TWI601969B - Method and apparatus for forecasting environmental status in a designated area - Google Patents

Description

Fixed environment state prediction method and device

The invention relates to weather forecasting technology, in particular to a method and a device for predicting a fixed-point environment state.

The emergence of Internet and satellite positioning technology has made it possible to provide personal location-based services. Internet weather forecasts have been freed from the shackles of TV programs. People can view the weather anytime and anywhere, but the timeliness and location accuracy of forecasts are still not available. A good solution, which led to the development of fixed-point rainfall forecasting technology.

The fixed-point weather forecast knows the user's location through the Global Positioning System (GPS) on the mobile phone, calculates the weather conditions of the location for a certain period of time, uses the icon to indicate the weather, and uses the weather map to map the location around the location. The weather conditions are indicated. The existing fixed-point weather forecasting technology can only provide weather conditions around the user, such as whether there is rain, whether there is any flaws, etc., and still can not meet the user's requirements for the accuracy of the forecast and the readability of the description. It is difficult for the user to intuitively obtain the desired information. The information you want.

The slang and songs about the weather and the environment are well-known, but it was not until the establishment of modern meteorology in the 18th century that scientific weather forecasts were available. Until today, the mainstream weather forecast is still in the form of weather consultations, with artificial weather forecasters, a variety of numerical models to publish a city weather conditions for a certain period of time. However, the size of a city is large, and the rain on the west side of the east side occurs from time to time. Moreover, manual release requires judgment and process, and the release timeliness is not high enough, sometimes it cannot keep up with the weather changes. The description of artificial weather forecast is difficult to be accurate. .

A first aspect of the present invention provides a method for predicting a fixed-point environment state, comprising: acquiring geographic location information of a user, acquiring environmental state forecast data within a preset time range of the geographic location, and generating the geographic location according to the environmental state forecast data. An environmental state prediction curve in the preset time range, acquiring an environmental state change point on the environmental state prediction curve, and generating an environmental state forecast statement in the preset time range according to the environmental state change point, The environmental status prediction statement is pushed to the user. By pushing the environment state prediction information within the preset time range described by the natural language to the user, the user can intuitively see the specific time when the environmental state changes within the preset time range.

A second aspect of the present invention provides a method for predicting a fixed-point environment state, comprising: acquiring geographic location information of a user; acquiring an environmental state quantization value matrix of the geographic location preset region, the environmental state quantization value matrix and the preset region Corresponding to the environmental state quantized value of each sub-region; determining a sub-region in which the user is located in the preset region, and a point corresponding to the user in the matrix of environmental state quantization values; determining the pre- a sub-region in which an environmental state quantized value is greater than zero in the region; determining an azimuth relationship between the sub-region in which the environmental state quantized value is greater than zero and the sub-region in which the user is located; and the preset region The environmental state of the sub-area in which the environmental state quantized value is greater than zero and the azimuth relationship between the sub-area in which the environmental state quantized value is greater than zero and the sub-area in which the user is located are combined into an environmental state forecast statement; The environmental status prediction statement is pushed to the user. By pushing the environment state prediction information within the preset area described by the natural language to the user, the user can intuitively see the specific location of the environmental state distribution that the user cares about within the preset area.

A third aspect of the present invention provides a fixed-point environment state prediction apparatus, including: an acquisition module, configured to acquire geographic location information of a user and environmental state prediction data within a preset time range of the geographic location; and a processing module, configured to The environmental state prediction data generates an environmental state prediction curve of the geographic location within the preset time range, acquires an environmental state change point on the environmental state prediction curve, and generates the pre-preparation according to the environmental state change point The environment state forecast statement in the time range is set; the sending module is configured to push the environment state forecast statement to the user.

A fourth aspect of the present invention provides a device for predicting a fixed-point environment state, comprising: an obtaining module, configured to acquire a geographic location information of a user and a matrix of environmental state quantized values of the geographic location preset region, and the matrix of the environmental state quantized value Corresponding to the environmental state quantized value of each sub-area in the preset area; the processing module is configured to determine a sub-area in which the user is located in the preset area, and the user quantizes in the environmental state a corresponding point in the value matrix; determining a sub-area in which the environmental state quantization value is greater than zero in the preset area; determining a sub-area in which the environmental state quantization value is greater than zero and the sub-area in which the user is located An orientation relationship between the sub-areas in which the environmental state quantized value in the preset area is greater than zero and the sub-area in which the environmental state quantized value in the preset area is greater than zero and the sub-area in which the user is located The orientation relationship is combined into an environmental state prediction statement; and the sending module is configured to push the environmental state prediction statement to the user.

Based on the above, the fixed-point environment state prediction method and apparatus provided by the present invention automatically generates a natural language description of the environmental state of the location of the user, and by pushing the environment state prediction information described by the natural language to the user, the user can intuitively see the The specific time at which the environmental state changes within the time range and/or the specific location of the environmental state distribution that the user cares about within the preset region. Compared with the prior art, the accuracy of the forecast and the readability of the description are improved, and the user can intuitively obtain the desired information from it.

The above described features and advantages of the invention will be apparent from the description and appended claims appended claims

The fixed-point environment state prediction method provided by the embodiment of the present invention can be specifically applied to the process of performing environmental state prediction through a client terminal, which can be implemented by a fixed-point environment state prediction device, which can be integrated in a client terminal or Separately, the fixed-point environmental condition prediction device can be implemented by software and/or hardware. The client terminal may specifically be a computer, a smart phone, a tablet computer, a set-top box, a car navigation device, and the like.

FIG. 1 is a flowchart of a method for predicting a fixed-point environment state according to an embodiment of the present invention. As shown in FIG. 1 , the method for predicting a fixed-point environment state provided by this embodiment includes:

Step 10: acquiring geographic location information of the user;

Specifically, the location information of the user is obtained by locating the client terminal. It should be noted that the manner of obtaining the geographic location information of the user in this embodiment includes, but is not limited to, GPS satellite positioning, network positioning, mobile communication technology positioning, and scene recognition positioning. The corresponding positioning method is selected according to the type of the client terminal.

Step 20: Obtain environmental state forecast data in the preset time range of the geographic location;

Specifically, the environmental status forecast data is specifically precipitation forecast data, temperature forecast data, air quality forecast data, wind direction and wind speed forecast data. The fixed-point environment forecasting device can obtain the environmental state forecast data within the preset time range of the geographical location by accessing the Internet or the like.

Step 30: Generate an environmental state prediction curve of the geographic location within the preset time range according to the environmental state forecast data.

Wherein, the precipitation forecast curve indicates a situation in which the precipitation amount changes with time in the preset time range.

Step 40: Obtain an environmental state change point on the environmental state prediction curve;

For example, the environmental state change point may be a point at which the precipitation changes from zero to greater than zero or from greater than zero to zero, and the precipitation decreases from a large start to a small or small start, or the temperature begins to decrease. Or a similar state change point, such as a point that rises from a low point.

Step 50: Generate an environmental state prediction statement in the preset time range according to the environmental state change point;

Specifically, information such as time included in the environmental state change point, environmental state change trend, and the like may be extracted, and the information is combined to generate an environmental state forecast statement.

Step 60: Push the environmental status prediction statement to the user.

Specifically, the fixed-point environment state prediction device may send the environmental state prediction statement to the user terminal of the user, display the display interface of the client terminal, or send a text message to the user, and may also generate the generated environmental state by means of voice broadcast. The prediction statement is broadcast to the user, and the voice status report can be performed while displaying the environmental status prediction statement on the display interface of the client terminal. This embodiment does not limit this.

The fixed-point environment state prediction method provided by the embodiment automatically generates a natural language description of the environment state of the user's location, and by pushing the environment state prediction information described by the natural language to the user, the user can intuitively see the preset time range. The specific time when the environmental status changes. Compared with the prior art, the accuracy of the forecast and the readability of the description are improved, and the user can intuitively obtain the desired information from it.

The invention is further described by taking a fixed-point precipitation forecasting method as an example. These examples are for illustrative purposes and are not intended to limit the invention.

FIG. 2 is a flowchart of a method for predicting a fixed point precipitation according to an embodiment of the present invention. As shown in FIG. 2, the fixed-point precipitation forecasting method provided in this embodiment includes:

Step 11, obtaining geographic location information of the user;

Step 12: Obtain precipitation forecast data within the preset time range of the geographic location.

Specifically, the fixed-point precipitation forecasting device can obtain precipitation forecast data within the preset time range of the geographical location by accessing the Internet, for example, by accessing Google's weather forecasting application design development interface (API), weather weather of the weather station. The forecast API and other weather forecast interfaces obtain weather data. Of course, the method for obtaining precipitation forecast data in this embodiment is not limited thereto. The preset time range may be fixedly set by the system, or may be set by the user inputting a query request through the client terminal, and the preset time range may be specifically in hours, days, weeks, or months, and the current time point. For the beginning of time.

Step 13: Generate a precipitation forecast curve of the geographic location within the preset time range according to the precipitation forecast data.

Wherein, the precipitation forecast curve indicates a situation in which the precipitation amount changes with time in the preset time range.

In step 14, the precipitation state change point on the precipitation forecast curve is obtained.

Specifically, the precipitation state change point may be a point at which the precipitation changes from zero to more than zero or from more than zero to zero, and the amount of precipitation becomes smaller from a large start or becomes larger from a small one.

In other words, if the precipitation forecast curve is regarded as a function image of the amount of precipitation over time in the preset time range, the precipitation state change point is the inflection point on the function image.

Step 15: Generate a precipitation forecast statement within the preset time range according to the precipitation state change point.

Specifically, information such as the time included in the change point of the precipitation state, the trend of the precipitation change, and the like can be extracted, and the information is combined to generate a precipitation forecast statement.

In step 16, the precipitation prediction statement is pushed to the user.

Specifically, the specific push mode can be selected according to the difference of the precipitation forecast statement. For example, if there is no precipitation state change point on the precipitation forecast curve, that is, if there is no precipitation state change within the preset time range, the precipitation interface is displayed on the display interface of the client terminal; if there is precipitation on the precipitation forecast curve The state change point, that is, the precipitation state change in the preset time range, displays the precipitation forecast statement on the display interface of the client terminal, and broadcasts the precipitation forecast statement to the user.

In addition, the generated precipitation prediction curve of the geographical location within the preset time range may also be sent to the user terminal of the user, and displayed on the display interface of the client terminal for reference by the user.

The fixed-point precipitation forecasting method provided by the embodiment combines the information to generate precipitation in a natural language because the precipitation state change point obtained according to the corresponding precipitation forecast curve includes information such as corresponding time and precipitation change trend. The forecast statement allows the user to visually see the specific time when the precipitation state changes within the preset time range. The accuracy of the forecast and the readability of the description are improved, and the user can intuitively obtain the desired information.

The fixed-point precipitation prediction method provided in this embodiment may further include the following steps on the basis of the embodiment shown in FIG. 2:

Receiving a precipitation forecast request message sent by the user.

Specifically, when the user wants to obtain the precipitation forecast information of a certain time range of the geographical location, the user terminal may send a precipitation forecast request message to the fixed point precipitation forecasting device. After receiving the precipitation forecast request message sent by the user, the fixed-point precipitation forecasting device acquires the geographical location information of the user and the precipitation forecast data within the preset time range of the geographical location, and finally generates a precipitation forecast statement, and sends the precipitation forecast statement to the user.

Optionally, when sending the precipitation forecast request message, the user may request the fixed-point precipitation forecasting device to predict the precipitation forecast in a certain time range in the future. In other words, the user can set the preset time range.

Further, in this embodiment, in step 13, the precipitation prediction curve of the geographic location in the preset time range is generated according to the precipitation forecasting data, which may specifically include the following steps:

And generating, by the interpolation method, the precipitation forecast data set of the geographical location within the preset time range;

Suppose that the predicted rainfall is a series of points (x, .y), where x and y are both real numbers, y is the size of the rainfall, and x is the time. It can be assumed that the unit of unit rainfall is mm/hr and the unit of time is minutes. Then (5,.15) indicates that the rainfall after 5 minutes is 15 mm/hour. If we have two predicted rainfalls, they can be represented by coordinates (x ₀ ,.y ₀ ), (x _l ,.y _l ), and the rainfall between x ₀ time and x ₁ time can be obtained by interpolation. This embodiment is schematically illustrated by a linear interpolation example.

3 is a schematic diagram of a linear interpolation method according to an embodiment of the present invention. Referring to FIG. 3, it is assumed that coordinates (x ₀ , .y ₀ ), (x _l , .y _l ) are known, and (x ₀ , .x _{1 is obtained.} The value of a position x on a straight line in the interval. According to Figure 3, it can be concluded that:

Since the value of x is known, the value of y can be obtained from the formula:

It should be noted that the accuracy of the precipitation forecast data set in time is a preset value, and it can be understood that the accuracy of the precipitation forecast data set in time is the forecast of precipitation per minute, the forecast of precipitation every five minutes, and the like. It is apparent that the above examples are in minutes as a time unit for illustrative purposes only and are not intended to limit the invention. It can be understood that, assuming that the preset time range is set to be two weeks in the future, the corresponding hour or day can be selected as the time unit, and the corresponding rainfall unit can be mm/hr or mm/day. The interpolation method used in this embodiment may be a conventional difference method such as a linear interpolation algorithm, a cubic spline interpolation algorithm, and an Hermitian interpolation algorithm, which is not limited in this embodiment.

And generating the precipitation forecast curve according to the set of precipitation forecast data.

Obviously, the time interval of precipitation forecast data within the preset time range of the obtained geographical location is relatively large, and the time precision requirement for detailed precipitation forecast cannot be satisfied. In general, the precipitation forecast data of the geographic location for the next three hours through the weather forecast API of the meteorological observatory is the forecast data of the precipitation corresponding every half hour. After the interpolation method, the precipitation forecast data corresponding to every five minutes can be obtained. It can be understood that when the time precision is preset to one minute or ten minutes, correspondingly, the precipitation forecast data corresponding to one minute or ten minutes can be obtained by the interpolation method. The precipitation forecast data for the next three hours of the geographic location every five minutes (or one minute/ten minute) constitutes a set of precipitation forecast data. In this way, the precipitation forecast curve can be generated according to the set of precipitation forecast data.

In practical applications, interpolation algorithms such as linear interpolation, cubic spline interpolation, and Hermitian interpolation can be used. In this embodiment, preferably, a cubic spline interpolation algorithm is used to process the generated precipitation prediction curve. It can be understood that the precipitation prediction curve generated by the cubic spline interpolation algorithm is smoother than the precipitation prediction curve generated by the linear interpolation algorithm, and the accuracy of the precipitation prediction data set processed by the cubic spline interpolation algorithm is better. .

Further, in this embodiment, in step 14, the precipitation state change point on the precipitation prediction curve is obtained, which may specifically include the following steps:

Obtaining, in the set of precipitation forecast data, a first-order difference absolute value of the precipitation is less than a first-order differential threshold, and a second-order difference absolute value is greater than a second-order differential threshold value;

Specifically, the first-order differential threshold and the second-order differential threshold may be preset, and the first-order differential threshold and the second-order differential threshold are both positive numbers. Obtaining the first-order difference sequence and the second-order difference sequence corresponding to the precipitation sequence in the precipitation forecast data set, and sequentially comparing the magnitude relationship between the first-order difference absolute value and the first-order difference threshold value, the second-order difference absolute value and the second-order difference threshold value The first order difference absolute value is smaller than the first order difference threshold value, and the second order difference absolute value is greater than the second order difference threshold value.

Among the change points, the time interval from the previous change point is greater than the preset time threshold, and the change point of the precipitation interval from the previous change point is greater than the preset precipitation amount threshold as the precipitation state change point.

Specifically, the minimum time interval may be preset as the time threshold and the minimum rainfall interval as the precipitation threshold. According to the first-order difference absolute value is less than the first-order differential threshold value, and the second-order difference absolute value is greater than the second-order difference threshold value to find the above change point, the change point closest to the current time point can be selected as the first precipitation state change point, and then sequentially calculated. The time interval between the subsequent change point and the previous change point and the precipitation interval, find that the time interval from the previous change point is greater than the preset time threshold, and the precipitation interval from the previous change point is greater than the preset precipitation The change point of the threshold is used as a point of change of other precipitation states.

If the precipitation forecast curve is regarded as a function image of the amount of precipitation over time in the preset time range, the precipitation state change point is the inflection point on the function image. The precipitation forecast data set can also be regarded as a function of the precipitation change with time in the preset time range. Obviously, this is a discrete function, and the discrete function inflection point algorithm can be used to obtain the precipitation forecast data set. The state change point in .

In this embodiment, mathematical definitions are used, and other methods may be used to define the points at which the precipitation trend on the precipitation prediction curve changes.

Further, in this embodiment, in step 15, the precipitation prediction statement in the preset time range is generated according to the precipitation state change point, which may specifically include the following steps:

If there is no precipitation state change point on the precipitation forecast curve, combining the preset time range with the current precipitation amount as the precipitation forecast statement;

If there is a precipitation state change point on the precipitation forecast curve, the precipitation change trend between the current time point and the adjacent two points in the precipitation state change point is sequentially determined, and the current time point and the precipitation state change point are determined. The trend of the precipitation change between the adjacent two points and the time corresponding to the change point of the precipitation state are sequentially combined into the precipitation forecast statement.

Specifically, if there is no precipitation state change point on the precipitation forecast curve, the current precipitation amount and the preset time range are combined into a precipitation forecast statement according to the current precipitation amount and a preset time range, for example, when the preset time range is For three hours, the current precipitation is greater than zero, and the precipitation forecast statement can be generated as "there is rain for the next three hours", or it can be described as "the rain will last for three hours" and the like. That is, a combination of the current current precipitation amount and the preset time range may be set in the fixed-point precipitation forecasting device to generate a precipitation forecast statement. Further, some other factors may also be considered, and some humanized prompt statements may be added to the precipitation forecast statement. For example, "There will be rain in the next three hours, go out and remember to bring rain gear!", "It will snow in the next two hours, please pay attention to antifreeze!", etc., for example, taking into account time factors, such as at night (between 23 and 6 am) ), the precipitation forecast statement can be "I won't rain in the next three hours, still working overtime, pay attention to rest!" The specific description of the precipitation forecast statement is not limited to this embodiment.

If there is a precipitation state change point on the precipitation forecast curve, information such as the time included in the precipitation state change point and the change trend of the precipitation amount may be extracted. Combine this information to generate precipitation forecast statements. Specifically, it is necessary to first determine a trend of precipitation change between two points in the current time point and the change point of the precipitation state, and then extract the judgment result, and sequentially combine the corresponding time information and the judgment result into the precipitation forecast statement. .

In order to further illustrate the fixed-point precipitation prediction method provided by the embodiment, an example will be described below. This example is only used to illustrate the fixed point precipitation forecasting method provided by this embodiment, and is not limiting.

It is assumed that, by steps 11-14, the precipitation prediction curve of the geographical location within the preset time range and the precipitation state change point on the precipitation prediction curve are A(t ₁ , .v ₁ ), B(t ₂ , .0), where the coordinates of the two points A and B correspond to the time and precipitation of the point, and the current time point is O(0,.v ₀ ), where 0 <v ₀ <v ₁ . Firstly, the trend of precipitation between the current time point O(0,.v ₀ ) and the state change point A(t ₁ ,.v ₁ ) is changed as the precipitation starts to increase from small to small; then the state change point A is judged. _The change trend of precipitation between ₁ , .v ₁ ) and state change point B (t ₂ , .0) is that the precipitation decreases from large to small until the rain stops. The time information corresponding to the precipitation change point A and B is t ₁ minute and t ₂ minute respectively, and the judgment result and the time corresponding to the precipitation state change points A and B are sequentially combined into a precipitation forecast statement, which can be described as “now raining It becomes bigger, and after ₁ minute, the rain starts to get smaller, until the rain stops after t ₂ minutes.

Further, in this embodiment, the fixed point precipitation forecasting method further includes the following steps:

A mapping relationship between the precipitation amount and the precipitation level is generated; and the precipitation amount in the precipitation prediction statement is represented by a corresponding precipitation level.

Specifically, the level of precipitation is: 0—no rain, less than 0.25 mm/hour of precipitation; 1—light rain, precipitation between 0.25 and 1.0 mm/hr; 2—rainfall, precipitation between 1.0 and 4.0 Between mm/hr; 3—heavy rain, precipitation between 4.0 and 16.0 mm/hr; 4—storm, precipitation greater than 16.0 mm/hr.

The mapping relationship between the precipitation amount and the precipitation level is constructed, the precipitation amount is mapped to the level interval of the corresponding precipitation amount, and the precipitation amount in the precipitation prediction statement is represented by the corresponding precipitation level. When there is no precipitation state change point on the precipitation forecast curve within the preset time range (for example, three hours), the current precipitation amount is mapped to the corresponding precipitation level range, for example, the current precipitation amount is 15 mm/hour. The grade interval mapped to the magnitude of the precipitation corresponds to heavy rain, and the precipitation forecast statement can be described as "there is heavy rain for the next three hours." The specific description of the precipitation forecast statement is not limited to this embodiment.

Correspondingly, when there is a precipitation state change point on the precipitation forecast curve within the preset time range, the above example can be continued. The rainfall at the current time point O(0,.v ₀ ) is mapped to the level interval of the precipitation amount, for example, v ₀ = 15 mm / hour, corresponding to heavy rain, the change point of the rainfall state A (t ₁ , .v ₁ ) The rainfall is mapped to the interval of the rainfall size, for example, v ₁ =17 mm / h, corresponding to the heavy rain, the rainfall state change point B (t ₂ , .0) of the rainfall maps to the level of the precipitation If there is no rain, the precipitation forecast statement can be described as "now it is heavy rain and heavy rain, after ₁ minute, the rainstorm begins to become smaller, until the rain stops after t ₂ minutes." The specific description of the precipitation forecast statement is not limited to this embodiment.

It is worth mentioning that the above-mentioned precipitation forecast statement may specifically be one of various combinations of precipitation change trend information, corresponding time information, and precipitation level, and there is no limitation on the specific combination manner or combination order.

The fixed-point precipitation forecasting method provided by the embodiment preprocesses the precipitation forecast data of the geographic location within the preset time range by using an interpolation method, and obtains a precipitation forecast of the geographic location within the preset time range. The data set, that is, the precipitation forecast data with higher time precision is obtained, and the corresponding precipitation forecast curve is generated according to the precipitation forecast data set, because the change of the precipitation state obtained according to the corresponding precipitation forecast curve includes the corresponding time and precipitation change. Trends and other information, combine these information to generate precipitation forecast statements in natural language, users can visually see the specific time when the precipitation state changes within the preset time range. Further, by constructing a mapping relationship between the precipitation amount and the precipitation level, the precipitation amount in the precipitation prediction statement is represented by a corresponding precipitation level, and the user can visually see the specific precipitation variation trend within the preset time range. In the form of natural language, the user is provided with a description of the start time of the precipitation and the change of the amount of precipitation, and the user can intuitively obtain the desired information.

The fixed-point precipitation prediction method provided by the above embodiment is further described in detail below through a specific example.

Assume that the precipitation forecast data for the next hour of the user's geographic location is: (0,.15), (10,.16), (20,.10), (30,.5), (40,.1), (50, .0), (60, .0).

The preset time precision is one minute, and the precipitation forecast data set is obtained by interpolation method: [15.00, 15.77, 16.36, 16.77, 17.03, 17.14, 17.12, 16.98, 16.74, 16.41, 16.00, 15.53, 15.00, 14.43, 13.83, 13.20, 12.55, 11.90, 11.25, 10.61, 10.00, 9.42, 8.86, 8.33, 7.82, 7.32, 6.85, 6.38, 5.92, 5.46, 5.00, 4.54, 4.08, 3.63, 3.19, 2.76, 2.35, 1.96, 1.61, 1.29, 1.00, 0.76, 0.55, 0.38, 0.25, 0.14, 0.07, 0.02, -0.01, -0.01, 0.00, 0.03, 0.06, 0.10, 0.13, 0.16, 0.18, 0.18, 0.15, 0.09].

According to the above precipitation forecast data set, a precipitation forecast curve for the next hour is generated as shown in FIG. 4, and FIG. 4 is a schematic diagram of a precipitation forecast curve according to an embodiment of the present invention.

Calculate the first-order difference sequence corresponding to the precipitation forecast data set: [0.77, 0.59, 0.41, 0.26, 0.11, -0.02, -0.14, -0.24, -0.33, -0.41, -0.47, -0.53, -0.57, -0.60 , -0.63, -0.65, -0.65, -0.65, -0.64, -0.61, -0.58, -0.56, -0.53, -0.51, -0.50, -0.47, -0.47, -0.46, -0.46, -0.46, - 0.46, -0.46, -0.45, -0.44, -0.43, -0.41, -0.39, -0.35, -0.32, -0.29, -0.24, -0.21, -0.17, -0.13, -0.11, -0.07, -0.05, -0.03, 0.00, 0.01, 0.03, 0.03, 0.04, 0.03, 0.03, 0.02, 0.00, -0.03, -0.06].

Calculate the second-order difference sequence corresponding to the precipitation forecast data set: [-0.18, -0.18, -0.15, -0.15, -0.13, -0.12, -0.10, -0.09, -0.08, -0.06, -0.06, -0.04, - 0.03, -0.03, -0.02, -0.00, 0.00, 0.01, 0.03, 0.03, 0.02, 0.03, 0.02, 0.01, 0.03, 0.00, 0.01, 0.00, 0.00, 0.00, 0.00, 0.01, 0.01, 0.01, 0.02, 0.02 , 0.04, 0.03, 0.03, 0.05, 0.03, 0.04, 0.04, 0.02, 0.04, 0.02, 0.02, 0.03, 0.01, 0.02, 0.00, 0.01, -0.01, 0.00, -0.01, -0.02, -0.03, -0.03] .

Let the first-order differential threshold be 0.1 and the second-order differential threshold be 0.02. The first-order difference absolute value is smaller than the first-order differential threshold, and the second-order difference absolute value is greater than the second-order differential threshold. The change points are: (5,.17.03) , (45, .0.25), (46,.0.14), (58,.0.18).

With a minimum interval of 5 minutes and a minimum rainfall interval of 1 mm/hr, the final precipitation change points are: (5, .17.03), (45, .0.25).

The grade of the amount of precipitation is 0: no rain, the precipitation is less than 0.25 mm / hour; 1 - light rain, precipitation is between 0.25 ~ 1.0 mm / hour; 2 - moderate rain, precipitation is 1.0 ~ 4.0 mm / hour 3; heavy rain, precipitation between 4.0 ~ 16.0 mm / h; 4 - heavy rain, precipitation is greater than 16.0 mm / h. Then, the precipitation level corresponding to the change point of the precipitation state is rainstorm and no rain, respectively.

The precipitation information corresponding to the current time point is (0, .15.00), and the corresponding precipitation level is heavy rain. It is determined in turn that the change trend of the precipitation between the current time point and the adjacent two points in the precipitation state change point is that the heavy rain turns to heavy rain and the heavy rain becomes small until the rain stops.

The resulting precipitation forecast statement can describe "it is now heavy rain and heavy rain, and after 5 minutes, the rain begins to get smaller until the rain stops after 45 minutes."

It can be understood that, in the embodiment not shown in the present invention, when the acquired environmental state is temperature forecast data, air quality forecast data, wind direction and wind speed forecast data, the processing process is similar to the precipitation forecast data processing process.

FIG. 5 is a flowchart of a method for predicting a fixed-point environment state according to another embodiment of the present invention. As shown in FIG. 5, the method for predicting a fixed-point environment state provided by this embodiment includes:

Step 21: Obtain geographic location information of the user;

For example, the method for obtaining the location information of the user by the client terminal can be referred to the foregoing embodiment, and details are not described herein again.

Step 22: Obtain an environment state quantization value matrix of the geographic location preset area, where the environmental state quantization value matrix corresponds to an environmental state quantization value of each sub-area in the preset area;

Specifically, the fixed-point environment state forecasting device may acquire the environmental state forecast data of the geographical location preset area by accessing the Internet or the like, and then quantize the environmental state forecast data to obtain the environmental state quantized value matrix. The quantitative value of the environmental state may specifically be precipitation, temperature, and fine particulate matter in the air.

Step 23: determining a sub-area in which the user is located in the preset area, and a point corresponding to the user in the matrix of the environmental state quantization value;

Step 24, determining a sub-area in which the environmental state quantization value in the preset area is greater than zero;

Step 25: Determine an orientation relationship between a sub-area in which the environmental state quantization value is greater than zero and a sub-area in which the user is located in the preset area;

Step 26: The environmental state of the sub-area in which the environmental state quantized value is greater than zero in the preset area and the sub-area in which the environmental state quantized value in the preset area is greater than zero and the sub-area in which the user is located , combined into an environmental state forecast statement;

In step 27, the environmental state prediction statement is pushed to the user.

Specifically, the environment state prediction statement is sent to the user terminal of the user, displayed on the display interface of the client terminal, and the text message may be sent to the user, and the generated environmental state prediction statement may be broadcast to the user by means of voice broadcast. The voice broadcast can be performed at the same time as the environment state prediction statement is displayed on the display interface of the client terminal, which is not limited in this embodiment.

The environmental state prediction method provided by the embodiment finally generates an environmental state prediction statement within a preset area range described by a natural language, and the user can intuitively see the preset by pushing the environmental state prediction information described by the natural language to the user. The specific location of the environment state distribution that the user cares about in the region. The accuracy of the forecast and the readability of the description are improved, and the user can intuitively obtain the desired information.

The invention is further described by taking a fixed-point precipitation forecasting method as an example. These examples are for illustrative purposes and are not intended to limit the invention.

FIG. 6 is a flowchart of a method for predicting a fixed point precipitation according to another embodiment of the present invention. As shown in FIG. 6, the fixed-point precipitation forecasting method provided in this embodiment includes:

Step 31: Obtain geographic location information of the user.

Step 32: Obtain a precipitation matrix of the geographic location preset area.

Specifically, the fixed-point precipitation forecasting device may obtain precipitation forecast data in the preset location of the geographical location by accessing the Internet, for example, obtaining weather data by accessing Google's weather forecast API, the weather forecast API of the weather station, and other weather forecast interfaces. Of course, the manner in which the present embodiment obtains precipitation forecast data is not limited thereto. The preset area is divided into a plurality of sub-areas of the same size, and the size of the sub-areas can be preset. Generating a precipitation matrix of the preset region according to the precipitation forecast data in the preset location of the geographic location corresponding to the precipitation amount of each sub-region, wherein the precipitation matrix and each sub-region of the preset region The amount of precipitation corresponds. The fixed-point precipitation forecasting device can also obtain the precipitation matrix by the prior art.

The preset area includes the geographic location of the user. Preferably, the province, the city, the district and the county where the user is located may be determined according to the administrative division, and then one of the provinces, cities, districts and counties is selected as the preset area.

Step 33: Determine a sub-region where the user is located in the preset area, and a point corresponding to the user in the precipitation matrix.

Specifically, the sub-area in which the user is located in the preset area may be determined according to the latitude and longitude corresponding to the edge of the preset area and the latitude and longitude corresponding to the location of the user. In order to describe the step more clearly, it is assumed that the user is located. The latitude and longitude corresponding to the position is [x ₁ , .y ₁ ], and the latitude and longitude corresponding to the edge of the preset area is [x ₂ , .x ₃ ]×[y ₂ ,.y ₃ ], and the precipitation matrix A of the preset region is obtained. The size is m×n, then the coordinates of the corresponding point O _ij in the precipitation matrix of the user can be expressed as:

;

And finding a point corresponding to the user in the precipitation matrix, and determining, according to a correspondence between the precipitation matrix and each sub-region in the preset region, determining, by the user, in the preset region. Sub-area.

Step 34: Determine a sub-area in which the amount of precipitation in the preset area is greater than zero.

In a preferred manner, the corresponding precipitation in the precipitation matrix is found to be greater than zero, and the corresponding relationship between the precipitation matrix and each sub-region in the preset region is determined. A sub-area with a precipitation greater than zero.

Step 35: Determine an orientation relationship between a sub-area in which the amount of precipitation in the preset area is greater than zero and a sub-area in which the user is located.

The orientation relationship may specifically be eight orientations of east, south, west, north, southeast, southwest, northeast, and northwest. Specifically, the preset area can be divided into eight quadrants of Zhengdong, Zhengxi, Zhengnan, Zhengbei, Southeast, Southwest, Northeast, and Northwest with the sub-region where the user is located as the center point, according to the child whose precipitation is greater than zero. The quadrant in which the region is located determines an orientation relationship between the sub-region in which the precipitation amount is greater than zero in the preset region and the sub-region in which the user is located.

Step 36: Combine the precipitation amount of the sub-area whose precipitation amount is greater than zero in the preset area and the orientation relationship between the sub-area where the precipitation amount is greater than zero in the preset area and the sub-area where the user is located, and combine the precipitation relationship into the precipitation. Forecast statement.

Specifically, a precipitation forecast statement combination template may be set to combine the precipitation information and the orientation relationship information. In a preferred embodiment, the precipitation forecast statement combination template can be set as: "you + orientation relationship information + precipitation information". It can be understood that when there are sub-regions whose precipitation amount is greater than zero in multiple orientations, the orientation relationships may be combined or separately described. For example, in the preset area, there are sub-areas with precipitation greater than zero in the southeast and northwest directions of the sub-area where the user is located. The precipitation forecast statement can be described as "you have rain in the southeast and northwest directions", and can also describe "You have rain in the southeast and you have rain in the northwest." The specific description of the precipitation forecast statement is not limited to this embodiment.

Optionally, when there is no sub-area with a precipitation greater than zero in the preset area, a fixed precipitation prediction statement is generated, for example, “No precipitation around you”. Of course, the specific description of the precipitation forecast statement is not limited to this embodiment.

Step 37: Push the precipitation forecast statement to the user.

Specifically, the specific push mode can be selected according to the difference of the precipitation forecast statement. For example, in the case where there is no precipitation in the preset area, the precipitation prediction statement is displayed on the display interface of the client terminal; in the case where there is precipitation in the preset area, the precipitation prediction statement is displayed on the display interface of the client terminal, and the precipitation prediction is also performed. The statement is broadcast to the user.

In addition, the precipitation distribution map in the preset area may be generated according to the precipitation amount matrix of the preset area, and the location of the user in the precipitation distribution map is marked according to the geographic location information of the user, and The precipitation profile is sent to the user terminal of the user and displayed on the display interface of the client terminal for reference by the user.

The fixed-point precipitation forecasting method provided by the embodiment finally generates a precipitation forecast statement in a preset area range described by a natural language, and the user can intuitively see the preset area range by pushing the precipitation forecast information described by the natural language to the user. The specific location of the internal precipitation distribution. The accuracy of the forecast and the readability of the description are improved, and the user can intuitively obtain the desired information.

Optionally, the fixed-point precipitation forecasting method provided in this embodiment is based on the embodiment shown in FIG. 6. In step 35, determining a sub-area in which the precipitation amount is greater than zero in the preset area and a sub-area in which the user is located The orientation relationship between the two may include the following steps:

Calculating a distance between the sub-area in which the precipitation amount is greater than zero in the preset area and the sub-area in which the user is located;

Determining an orientation relationship between a sub-region closest to the user and a sub-region in which the user is located in the sub-region in which the precipitation amount is greater than zero in the preset region.

According to step 34, a sub-area in which the precipitation amount is greater than zero in the preset area is determined. When there is more than one sub-area in the preset area where the amount of precipitation is greater than zero, preferably, the sub-area closest to the user and the user are located. The orientation relationship between sub-areas and their precipitation information are predicted to the user.

Specifically, according to the corresponding relationship between the precipitation matrix of the preset region and the precipitation amount of each sub-region, the corresponding point in the precipitation matrix and the corresponding point in the precipitation matrix of the sub-region with the precipitation greater than zero may be calculated. The Euclidean distance between the two is determined by comparing the points corresponding to the sub-region closest to the user in the precipitation matrix, thereby determining the sub-region closest to the user. The specific process of determining the azimuth relationship between the sub-area closest to the user and the sub-area in which the user is located is the same as that in the embodiment shown in FIG. 4, and details are not described herein again.

Further, the distance information between the sub-area closest to the user and the sub-area where the user is located may also be combined and predicted in the precipitation forecast statement to the user.

Further, the fixed-point precipitation prediction method provided in this embodiment is based on the embodiment shown in FIG. 4, and in step 35, determining a sub-area in which the precipitation amount is greater than zero in the preset area and a sub-area in which the user is located The orientation relationship between the two may further include the following steps:

Determining a point in the precipitation matrix that the precipitation is greater than zero;

Determining, by the first line of the line connecting the point corresponding to the user in the precipitation amount matrix, the first vector formed by the point where the precipitation amount is greater than zero;

And determining, according to the quadrant of the first vector, an orientation relationship between the sub-area in which the precipitation amount is greater than zero and the sub-area in which the user is located.

Specifically, it can be schematically illustrated by the following examples. Assume that the point where the precipitation in the precipitation matrix is greater than zero is P(a,.b). It can be understood that the point P is located in the ath row and the bth column of the precipitation matrix. Assuming that the user's location is in the corresponding point O(i,.j) in the precipitation matrix, in the i-th row and the j-th column in the precipitation matrix, the first vector formed by the connection of the point P and the point O may Expressed as And determining, according to a quadrant of the first vector, an orientation relationship between the sub-area in which the precipitation amount is greater than zero and the sub-area in which the user is located. The positive direction of the horizontal axis represents the true east, the negative direction of the horizontal axis represents the positive west, the positive direction of the vertical axis represents the true north, the negative direction of the vertical axis represents the positive south, and the interval between the east and the north represents the northeast direction, and the east and the positive The interval between the south indicates the southeast direction, the interval between the west and the north indicates the northwest direction, and the interval between the west and the south indicates the southwest direction.

Further, the fixed-point precipitation prediction method provided in this embodiment further includes the following steps on the basis of the embodiment shown in FIG. 6:

Obtaining a wind direction field matrix of the geographic location preset area.

In this embodiment, the wind direction matrix may also obtain the wind direction and wind speed information of the preset area according to the weather forecast data of the preset area by acquiring the same amount of precipitation matrix, and then according to the wind direction matrix and the preset area. A wind direction field matrix is generated corresponding to each sub-area, and the wind direction field matrix corresponds to a wind direction and a wind speed of each sub-area in the preset area. For example, the wind direction field matrix is represented as B(i, j, k)=wind_speed, where i, j represents the corresponding coordinate of the sub-region in the wind direction matrix, k is 0 or 1, and k=0 is the east-west direction. k=1 indicates the north-south direction. The wind direction field is in meters per second. The fixed point precipitation forecasting device can also obtain the wind direction field matrix by the prior art. It can be understood that the points in the wind direction matrix are in one-to-one correspondence with the points in the precipitation matrix.

Correspondingly, it is further determined that the amount of precipitation in the preset area is greater than zero and the wind direction is toward the sub-area of the user; determining that the amount of precipitation in the preset area is greater than zero and the wind direction is toward the sub-area of the user and the user An orientation relationship between the sub-regions in which the sub-regions are located; a precipitation amount in the preset region that is greater than zero and a wind direction toward the sub-region of the user, a precipitation amount in the predetermined region is greater than zero, and a wind direction toward the The orientation relationship between the sub-area of the user and the sub-area in which the user is located is combined into the precipitation forecast statement, and the precipitation forecast statement can be described as, for example, "you are raining in the northwest," and then pushed to the user. The specific description of the precipitation forecast statement is not limited to this embodiment.

Specifically, the following steps may be used to determine that the amount of precipitation in the preset area is greater than zero and the wind direction is toward the sub-area of the user.

a point in the precipitation matrix in which the amount of precipitation is greater than zero;

Determining, by the first line of the line connecting the point corresponding to the user in the precipitation amount matrix, a first vector formed by the line of the precipitation amount greater than zero, and the point where the precipitation amount is greater than zero in the wind direction field matrix a second vector of wind direction and wind speed;

The sub-region corresponding to the point at which the inner product of the first vector and the second vector is greater than zero is determined to be a sub-region in which the amount of precipitation in the preset region is greater than zero and the wind direction is toward the user.

The sub-region corresponding to the point at which the inner product of the first vector and the second vector is greater than zero is determined to be a sub-region in which the amount of precipitation in the preset region is greater than zero and the wind direction is toward the user.

For the implementation of the first vector that is determined by the connection of the point where the amount of precipitation is greater than zero, the line connecting the point corresponding to the user in the precipitation amount matrix, refer to the foregoing embodiment, and details are not described herein again.

In this embodiment, the point where the amount of precipitation is greater than zero forms a second vector in the wind direction and the corresponding wind speed in the wind direction matrix, which can be illustrated by an example. For example, the point P in which the precipitation amount in the precipitation matrix is greater than zero corresponds to the wind direction and the wind speed in the wind direction matrix, the wind speed from east to west is 10 m/s, and the wind speed from south to north is 5 m/s. a second vector formed by the corresponding wind direction and wind speed at a point where the precipitation amount is greater than zero, that is, the air flow motion vector can be expressed as .

If the angle between the first vector and the second vector obtained by the above is between [-90, 90], it is determined that the sub-region corresponding to the point corresponding to the second vector is that the precipitation in the preset region is greater than zero and The wind direction is towards the sub-area of the user. In this embodiment, it can be described by a mathematical method. The angle between the first vector and the second vector is between [-90, 90], and the inner product of the first vector and the second vector can be Judging greater than zero.

Further, in this embodiment, the amount of precipitation in the preset area is greater than zero and the wind direction is toward the sub-area of the user, the amount of precipitation in the preset area is greater than zero, and the wind direction is toward the user. The orientation relationship between the sub-area and the sub-area in which the user is located may be included in the following steps before being combined into the precipitation prediction statement:

A distance between the sub-area in the preset area where the amount of precipitation is greater than zero and the wind direction is toward the user and the sub-area in which the user is located is calculated.

Correspondingly, the amount of precipitation in the preset area is greater than zero and the wind direction is toward the sub-area of the user, the amount of precipitation in the preset area is greater than zero, and the wind direction is toward the sub-area of the user and the user. The orientation relationship between the sub-regions in which the sub-regions are located, the distance between the sub-regions in the predetermined region and the sub-regions in which the wind direction is toward the user, and the sub-region in which the user is located are combined into the precipitation forecast. The statement, the generated precipitation forecast statement can be described, for example, as "you are approaching the rain in the northwest s km" and then push it to the user. The specific description of the precipitation forecast statement is not limited to this embodiment.

Specifically, the number of kilometers corresponding to the unit length of the precipitation matrix may be calculated according to the correspondence between the precipitation matrix and each sub-region in the preset region. Assume that the latitude and longitude corresponding to the edge of the preset area is [x2,.x3]×[y2,.y3], and the size of the precipitation matrix A of the preset area is m×n, then the number of kilometers corresponding to the unit length of the precipitation matrix for:

Among them, C _earth is the circumference of the earth.

The Euclidean distance r between the point corresponding to the sub-region of the user's sub-region in the precipitation matrix greater than zero and the wind direction toward the sub-region in which the user is located is then calculated. Then, the distance s between the sub-area in the preset area and the sub-area in which the wind direction is toward the user and the sub-area in which the user is located can pass Calculated.

Optionally, the precipitation in the preset area may be selected to be greater than zero and the wind direction is toward the sub-area of the user and the maximum precipitation in the adjacent sub-area as the corresponding precipitation information in the precipitation prediction statement.

Further, in this embodiment, the fixed point precipitation forecasting method further includes the following steps:

A mapping relationship between the precipitation amount and the precipitation level is generated; and the precipitation amount in the precipitation prediction statement is represented by a corresponding precipitation level.

In this embodiment, a mapping relationship between the precipitation amount and the precipitation level is generated, and the precipitation amount in the precipitation prediction statement is represented by a corresponding precipitation level, and the specific embodiment and the generated precipitation amount and precipitation in the foregoing embodiment of the present invention. The mapping relationship of the levels is similar to that of the precipitation in the precipitation forecast statement using the corresponding precipitation level, and is not described here. The generated precipitation forecast statement can be described, for example, as "you have heavy rain in the northwest", "you have heavy rain in the northwest of the s-kilometer", and "there is heavy rain in the northwest of the s-kilometer is approaching". That is to say, the above-mentioned precipitation forecast statement is one of various combinations of information such as corresponding orientation information, corresponding distance information, and precipitation level, and the specific combination mode or combination order is not limited, and the specific description of the precipitation forecast statement is also It is not limited to this embodiment.

The fixed-point precipitation forecasting method provided by the embodiment finally generates a precipitation forecast statement in a preset region range described by a natural language, and the user can not only know the distribution orientation of the precipitation zone but also understand the precipitation by describing the precipitation forecast information. The distance between the belt and the user, whether the precipitation belt is approaching the user, and the precipitation level of the precipitation belt. The rainfall is represented by different colors with respect to the prior art, and a graphical depiction of the direction of movement of the rainband is indicated by arrows. The natural language description mode provided by the invention improves the accuracy of the forecast and the readability of the description, and the user can intuitively obtain the desired information from the user.

The fixed-point precipitation prediction method provided by the embodiment shown in FIG. 6 is further described in detail below by a specific example.

Assume that the geographic location information of the user is E120.25 and N23.25, and the latitude and longitude corresponding to the edge of the preset location of the user's geographic location is [E120.0, .E120.5]×[N23.0, .N23.5].

Assume that the precipitation matrix A of the preset location of the user's geographic location is obtained as:

Assume that the wind direction field matrix B of the preset location of the geographic location of the user is: B(2, 9, 0)=10, B(2, 9, 1)=-10, B(3, 9, 0)=10, B(3, 9, 1)=10, B(i, j, k)=0, where i,j represents all the remaining points.

Obviously, the magnitude of the precipitation matrix A is 10×10, that is, m=n=10. Therefore, the coordinates of the user's location in the rainfall matrix and the number of kilometers corresponding to the length of the rainfall matrix are calculated by the formula:

That is, the coordinates of the user in the precipitation matrix are (5, 5), and the number of kilometers corresponding to the unit length of the rainfall matrix is 5.69 kilometers.

The points corresponding to the sub-areas whose rainfall is greater than zero in the precipitation matrix are determined to be (2, 9), (3, 9), (4, 9), (3, 8), (4, 8).

Determining that the amount of precipitation in the preset area is greater than zero and the wind direction is toward a sub-area of the user. First, find the points corresponding to the sub-areas where the wind speed is not zero in the sub-area where the rainfall is greater than zero (2, 9), (3, 9).

Specifically, the user position connection vector corresponding to the point (2, 9), that is, the first vector is (3, -4), and the airflow motion vector of the sub-region corresponding to the point (2, 9), that is, the second vector is ( 10, -10). The inner product of the first vector and the second vector corresponding to the calculation point (2, 9) is 70, so that the sub-region corresponding to the determination point (2, 9) is that the precipitation in the preset region is greater than zero and the wind direction is toward the user. Sub-area.

Specifically, the user position connection vector corresponding to the point (3, 9), that is, the first vector is (2, -4), and the airflow motion vector of the sub-region corresponding to the point (3, 9), that is, the second vector can be respectively Expressed as (10, 10). After the calculation point (3, 9) corresponds to the inner product of the first vector and the second vector is -20, it is determined that the sub-region corresponding to the point (3, 9) is not the precipitation in the preset region is greater than zero and the wind direction is toward the The sub-area of the user.

It can be determined that the sub-region corresponding to the point (2, 9) is a sub-region in which the precipitation in the preset region is greater than zero and the wind direction is toward the user.

Calculate the Euclidean distance r=5 between the point (2, 9) and the corresponding position of the user position in the precipitation matrix, according to the formula It can be calculated that the distance between the sub-area in the preset area where the amount of precipitation is greater than zero and the direction of the wind toward the user and the sub-area in which the user is located is approximately 28 kilometers.

The user position line vector corresponding to the point (2, 9), that is, the first vector is (3, -4), and the quadrant where the first vector is located is the area between the true west and the true north, and the judgment point (2, 9) The orientation relationship between the corresponding sub-area and the sub-area where the user is located is northwest.

The maximum precipitation in the sub-region corresponding to point (2, 9) and its adjacent sub-region is 16 mm / h, and the corresponding precipitation level is heavy rain.

The resulting precipitation forecast statement can be described as "the rainstorm is approaching 28 kilometers northwest."

It can be understood that, in the embodiment not shown in the present invention, when the acquired matrix of environmental state quantized values is temperature, the content of fine particles in the air, the processing thereof is similar to the process of acquiring the precipitation matrix.

FIG. 7 is a schematic diagram of a fixed-point environment state prediction apparatus according to an embodiment of the present invention. As shown in FIG. 7, the fixed-point environment state prediction apparatus 100 provided in this embodiment can implement the steps of the fixed-point environment state prediction method provided by the embodiment shown in FIG. 1 and the fixed-point precipitation prediction method provided by the embodiment shown in FIG. , will not repeat them here.

The fixed-point environment state prediction apparatus 100 provided in this embodiment specifically includes an acquisition module 101, a processing module 102, and a transmission module 103. The obtaining module 101 is configured to obtain geographic location information of the user and environmental state forecasting data within the preset time range of the geographic location. The processing module 102 is configured to generate an environmental state prediction curve of the geographic location within the preset time range according to the environmental state prediction data, and obtain an environmental state change point on the environmental state prediction curve, according to the environment. The state change point generates an environmental state prediction statement within the preset time range. The sending module 103 is configured to push the environmental status prediction statement to the user.

The fixed-point environment state prediction device provided by the embodiment obtains the geographic location information of the user and the environmental state prediction data in the preset time range of the geographic location by the acquiring module, so that the processing module generates the forecast data according to the environmental state. An environmental state prediction curve of the geographic location within the preset time range, acquiring an environmental state change point on the environmental state prediction curve, and generating an environmental state within the preset time range according to the environmental state change point The forecast statement is further pushed to the user by the sending module. The fixed-point environmental state forecasting device can combine the information according to the corresponding environmental state change curve to include the corresponding time and environmental state change trend, and generate the environmental state forecast statement described in the natural language. The user can intuitively see the specific time when the environmental status changes within the preset time range, and provide the information desired by the user in a relatively intuitive manner.

The environmental status prediction data acquired by the acquisition module 101 includes: precipitation forecast data, temperature forecast data, air quality forecast data, wind direction and wind speed forecast data.

FIG. 8 is a schematic diagram of a fixed-point environment state prediction apparatus according to still another embodiment of the present invention. As shown in FIG. 8, the fixed-point environment state prediction device 100 provided in this embodiment is based on the embodiment shown in FIG. 7. The fixed-point environment state prediction device 100 can also be provided with a receiving module 104 for receiving the receiving module. The environmental status prediction request message sent by the user. By setting the receiving module to receive the environmental status forecast request message sent by the user, the user can obtain the environmental status forecast information of the geographical location at any time and anywhere, and the user can also set the preset time range to be more convenient for the user to use.

In an actual application, the processing module 102 is specifically configured to generate, by using a linear interpolation method, the environmental state forecast data set of the geographic location within the preset time range, where the environmental state forecast is The accuracy of the data set in time is a preset value; and the environmental state prediction curve is generated according to the environmental state forecast data set.

In practical applications, the processing module 102 is further configured to query the environmental state forecast data set, wherein the first-order difference absolute value of the environmental state quantization value is smaller than the first-order differential threshold value, and the second-order difference absolute value is greater than the second-order differential threshold value. a change point, wherein the change point between the change point and the previous change point is greater than the preset time threshold, and the change from the environmental state quantized value of the previous change point is greater than the preset environmental state quantized value threshold The change in environmental status.

In an actual application, the processing module 102 is further configured to combine the preset time range and the current environmental state into an environmental state prediction statement when there is no environmental state change point on the environmental state prediction curve. When there is an environmental state change point on the environmental state prediction curve, the environmental state change trend between the current time point and the adjacent two points in the environmental state change point is sequentially determined, and the current time point and the environmental state are The change trend of the environmental state between two adjacent points in the change point and the time corresponding to the change point of the environmental state are sequentially combined into an environmental state forecast statement.

Further, the processing module 102 may be further configured to generate a mapping relationship between the environmental state quantization value and the environmental state level, and use the corresponding environmental state level to represent the environmental state in the environmental state prediction statement.

The fixed-point environment state forecasting device provided by the embodiment preprocesses the environmental state forecast data of the geographic location within the preset time range by using a processing module, and obtains that the geographic location is within the preset time range. The environmental state forecast data set, that is, the environmental state forecast data with higher time precision is obtained, and the corresponding environmental state forecast curve is generated according to the environmental state forecast data set, and the environmental state change point is obtained according to the corresponding environmental state forecast curve, and then the environment is The information contained in the state change point and the environmental state change trend are combined to generate an environmental state prediction statement described in a natural language, and the processing module also generates a mapping relationship between the environmental state and the environmental state level, and predicts the environmental state. The environment state in the statement is represented by the corresponding environment state level. Finally, the environment state prediction statement provided to the user by the sending module can intuitively display the specific time and/or specific trend of the environmental state change in the preset time range, and provide Give the user the information they want.

FIG. 9 is a schematic diagram of a fixed-point environment state prediction apparatus according to still another embodiment of the present invention. As shown in FIG. 9, the fixed-point environment state forecasting apparatus 200 provided in this embodiment can implement the steps of the fixed-point environment state forecasting method provided by the embodiment shown in FIG. 5 and the fixed-point precipitation forecasting method provided by the embodiment shown in FIG. , will not repeat them here.

The fixed-point environment state prediction apparatus 200 provided in this embodiment specifically includes an acquisition module 201, a processing module 202, and a transmission module 203. The obtaining module 201 is configured to obtain the geographic location information of the user and the environmental state quantization value matrix of the geographic location preset area, the environmental state quantization value matrix and the environmental state quantization value of each sub-area in the preset area correspond. The processing module 202 is configured to determine a sub-region where the user is located in the preset area, and a point corresponding to the user in the matrix of the environmental state quantization value; and determine an environment state quantization in the preset region a sub-region having a value greater than zero; determining an orientation relationship between the sub-region in which the environmental state quantization value is greater than zero and the sub-region in which the user is located; and the environmental state quantization value in the preset region is greater than The environmental state of the zero sub-area and the orientation relationship between the sub-area in which the environmental state quantization value is greater than zero and the sub-area in which the user is located are combined into an environmental state prediction statement. The sending module 203 is configured to push the environmental status prediction statement to the user.

Optionally, the processing module 202 is further configured to calculate a distance between the sub-area in which the environmental state quantization value is greater than zero in the preset area and the sub-area in which the user is located, and determine the preset area according to the calculation result. The orientation relationship between the sub-region closest to the user and the sub-region in which the user is located in the sub-region where the environmental state quantized value is greater than zero. Further, the processing module 202 may also combine the distance information between the sub-area closest to the user and the sub-area where the user is located in the environmental state prediction statement to predict the user.

The matrix of the environmental state quantization values acquired by the acquisition module 201 includes: a precipitation matrix, a temperature matrix, and a matrix of fine particle content in the air.

The fixed-point environment state prediction device provided by the embodiment obtains the geographic location information of the user and the environmental state quantization value matrix of the geographic location preset region by using the acquisition module, and the processing module obtains the preset region according to the environmental state quantization value matrix. The sub-area whose environmental state quantity is greater than zero and its orientation relationship with the sub-area where the user is located, and the environmental state of the sub-area whose environmental state quantized value is greater than zero in the preset area and the environmental state in the preset area are quantized The orientation relationship between the sub-region having a value greater than zero and the sub-region in which the user is located is combined into an environmental state prediction statement within a preset region range described in a natural language, and the user is pushed by the sending module to describe in a natural language. The environmental status forecast information provides the user with an intuitive distribution of the environmental status within the preset area, and the user can intuitively obtain the desired information.

The fixed-point environment state prediction apparatus 200 provided in this embodiment is based on the embodiment shown in FIG. 9. The processing module 202 is specifically configured to determine a point in the environmental state quantization value matrix that the environmental state quantization value is greater than zero; a first vector formed by a line connecting the point corresponding to the user in the environmental state quantized value matrix at a point where the environmental state quantized value is greater than zero; determining an environmental state in the preset area according to the quadrant of the first vector An orientation relationship between a sub-region having a quantized value greater than zero and a sub-region in which the user is located.

In an actual application, the obtaining module 201 is further configured to acquire a wind direction field matrix of the geographic location preset area, where the wind direction field matrix corresponds to a wind direction and a wind speed of each sub-area in the preset area.

Correspondingly, the processing module 202 is further configured to: determine that the environmental state quantization value in the preset area is greater than zero and the wind direction is toward the sub-area of the user; and determine that the environmental state quantization value in the preset area is greater than zero and the wind direction is oriented An orientation relationship between the sub-region of the user and the sub-region in which the user is located; an environmental state in which the environmental state quantization value in the preset region is greater than zero and the wind direction is toward the sub-region of the user, the pre-predetermined The orientation relationship between the sub-regions in which the environmental state quantized value in the region is greater than zero and the wind direction is toward the user and the sub-region in which the user is located is combined into the environmental state prediction statement.

In a practical application, the processing module 202 is further configured to: determine a point in the matrix of the environmental state quantized value matrix that the environmental state quantized value is greater than zero; and determine a point at which the environmental state quantity is greater than zero in the environmental state quantized value matrix a first vector formed by a line connecting the points corresponding to the user, and a second vector formed by the corresponding wind direction and wind speed of the point where the environmental state quantized value is greater than zero; determining the first vector The sub-region corresponding to the point where the inner product of the second vector is greater than zero is the sub-region in which the environmental state quantization value in the preset region is greater than zero and the wind direction is toward the user.

Further, the processing module 202 is further configured to calculate a distance between the sub-region where the environmental state quantization value in the preset region is greater than zero and the wind direction is toward the user and the sub-region where the user is located. Correspondingly, the processing module 202 is further configured to: the environmental state quantized value in the preset area is greater than zero and the wind direction is toward an environmental state of the sub-area of the user, and the environmental state quantized value in the preset area is greater than zero and The wind direction is oriented toward an orientation relationship between the sub-area of the user and the sub-area where the user is located, the environmental state quantization value in the preset area is greater than zero, and the wind direction is toward the sub-area of the user and the user is located The distance between the sub-regions is combined into the environmental state prediction statement.

Further, the processing module 202 is further configured to generate a mapping relationship between the environmental state quantization value and the environmental state level, and use the corresponding environmental state level to represent the environmental state in the environmental state prediction statement. The fixed-point environment state prediction device provided by the embodiment obtains the geographic location information of the user, the environmental state quantization value matrix of the geographical location preset area, and the wind direction field matrix, and the processing module quantizes the value matrix according to the environmental state. The wind direction field matrix obtains the sub-area whose environmental state quantized value is greater than zero in the preset area and the orientation information and distance information between the sub-area and the sub-area where the user is located, and judges that the environmental state quantized value in the preset area is greater than zero. Whether the area is approaching the user, the environment state of the sub-area whose environmental state quantized value is greater than zero in the preset area, and the sub-area where the environmental state quantized value in the preset area is greater than zero and the sub-area where the user is located The orientation information, the distance information, and whether the information is approached to the user, combined into an environmental state prediction statement within a preset area described by the natural language, and the environment state prediction information described by the natural language is pushed to the user through the sending module, and provided Give the user an intuitive orientation of the environment state of the user's concern in the preset area, Whether from environmental status of the user concerned about the state of the environment between the user and the user is concerned about the state of the environment closer to the user and the user's environment, care about state level and other information, the user can intuitively derive information you want.

One of ordinary skill in the art will appreciate that all or part of the steps of implementing the various method embodiments described above may be accomplished by hardware associated with the program instructions. The aforementioned program can be stored in a computer readable storage medium. When the program is executed, the steps of the foregoing method embodiments are performed; and the foregoing storage medium includes: various media that can store code, such as a ROM, a RAM, a disk, or a CD.

Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, and are not intended to be limiting; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that The technical solutions described in the foregoing embodiments may be modified, or some or all of the technical features may be equivalently replaced; and the modifications or substitutions do not deviate from the technical solutions of the embodiments of the present invention. range.

10 to 16, 20 to 27, 30 to 37, 40, 50, 60 ‧ ‧ steps
100, 200‧‧‧ fixed-point environmental status forecasting device
101, 201‧‧‧ acquisition module
102, 202‧‧‧ processing module
103, 203‧‧‧ transmit module
104‧‧‧ receiving module
x, x0, x1‧‧‧ time
y, y0, y1‧‧‧ rainfall size
(x,.y) ‧ ‧ a series of points
(x0,.y0), (xl,.yl)‧‧‧ coordinates

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are some embodiments of the present invention, Those skilled in the art can also obtain other drawings based on these drawings without paying progressive labor. FIG. 1 is a flowchart of a method for predicting a fixed-point environment state according to an embodiment of the present invention. FIG. 2 is a flowchart of a method for predicting a fixed point precipitation according to an embodiment of the present invention. FIG. 3 is a schematic diagram of a linear interpolation method according to an embodiment of the present invention. 4 is a schematic diagram of a precipitation prediction curve according to an embodiment of the present invention. FIG. 5 is a flowchart of a method for predicting a fixed-point environment state according to another embodiment of the present invention. FIG. 6 is a flowchart of a method for predicting a fixed point precipitation according to another embodiment of the present invention. FIG. 7 is a schematic diagram of a fixed-point precipitation forecasting device according to an embodiment of the present invention. FIG. 8 is a schematic diagram of a fixed point precipitation forecasting device according to another embodiment of the present invention. FIG. 9 is a schematic diagram of a fixed-point precipitation forecasting device according to still another embodiment of the present invention.

10, 20, 30, 40, 50, 60 ‧ ‧ steps

Claims (28)

A method for predicting a fixed-point environment state includes: acquiring geographic location information of a user; acquiring environmental state forecast data within a preset time range of the geographic location; generating the geographic location according to the environmental state forecast data at the preset time An environmental state prediction curve within the range; acquiring an environmental state change point on the environmental state prediction curve; generating an environmental state prediction statement within the preset time range according to the environmental state change point; and predicting the environmental state The statement is pushed to the user; wherein the environmental state prediction curve of the geographic location within the preset time range is generated according to the environmental state forecast data, including: passing the environmental state forecast data through a cubic spline interpolation method Generating an environmental state forecast data set of the geographic location within the preset time range, the accuracy of the environmental state forecast data set in time is a preset value; and generating the environment according to the environmental state forecast data set State forecast curve. The method for predicting a fixed-point environment state according to claim 1, wherein the obtaining the geographic location information of the user further comprises: receiving an environmental status prediction request message sent by the user. The method for predicting a fixed-point environmental state according to claim 1, wherein the obtaining the environmental state change point on the environmental state prediction curve comprises: acquiring the environmental state quantitative data value in the environmental state forecast data set. The first-order difference absolute value is smaller than the first-order difference threshold, and the second-order difference absolute value is greater than the second-order difference a change point of the threshold value; and a change point between the change point and the previous change point time interval being greater than the preset time threshold value, and the environmental state quantized value interval of the previous change point being greater than the preset environmental state quantized value threshold value As the point of change of the environmental state. The method for predicting a fixed-point environment state according to any one of the preceding claims, wherein the generating an environmental state forecast statement in the preset time range according to the environmental state change point includes: If there is no environmental state change point on the environmental state prediction curve, combining the preset time range with the current environmental state as the environmental state prediction statement; and if there is an environmental state change point on the environmental state prediction curve, And sequentially determining an environmental state change trend between the current time point and the adjacent two points in the environmental state change point, and changing an environmental state change trend between the current time point and the adjacent two points in the environmental state change point The time corresponding to the environmental state change point is sequentially combined into the environmental state prediction statement. The method for predicting a fixed-point environment state according to claim 4, further comprising: generating a mapping relationship between the environmental state quantization value and the environmental state level; and using the corresponding environmental state level for the environmental state in the environmental state prediction statement. Said. For example, the method for forecasting a fixed-point environmental state according to claim 1 of the patent scope includes: precipitation forecast data, temperature forecast data, air quality forecast data, wind direction and wind speed forecast data. A method for predicting a fixed-point environmental state includes: obtaining geographic location information of a user; Obtaining an environment state quantization value matrix of the geographic location preset area, where the environmental state quantization value matrix corresponds to an environmental state quantization value of each sub-area in the preset area; determining that the user is in the preset area a sub-region in which the user is located, and a corresponding point in the matrix of the environmental state quantization values; determining a sub-region in which the environmental state quantization value is greater than zero in the preset region; determining an environmental state in the preset region An orientation relationship between a sub-region having a quantized value greater than zero and a sub-region in which the user is located; an environmental state of the sub-region in which the environmental state quantized value is greater than zero in the preset region and an environmental state quantized value in the preset region An orientation relationship between a sub-region greater than zero and a sub-region in which the user is located is combined into an environmental state prediction statement; and the environmental state prediction statement is pushed to the user. The method for predicting a fixed-point environment state according to claim 7, wherein the determining a positional relationship between a sub-area in which the environmental state quantized value is greater than zero and a sub-area in which the user is located in the preset area, The method includes: calculating a distance between a sub-area in which the environmental state quantized value is greater than zero in the preset area and a sub-area in which the user is located; and determining a sub-area in which the environmental state quantized value in the preset area is greater than zero An orientation relationship between the sub-region closest to the user and the sub-region in which the user is located. The method for predicting a fixed-point environment state according to claim 7, wherein determining an orientation relationship between the sub-region in which the environmental state quantization value is greater than zero and the sub-region in which the user is located in the preset region includes: Determining that the environmental state quantization value in the environmental state quantization value matrix is greater than zero Determining a first vector formed by a line connecting the point corresponding to the user in the environmental state quantization value matrix at a point where the environmental state quantized value is greater than zero; and determining the location according to the quadrant of the first vector An orientation relationship between a sub-area in which the environmental state quantization value is greater than zero and the sub-area in which the user is located in the preset area. The method for predicting a fixed-point environment state according to any one of the preceding claims, further comprising: obtaining a wind direction field matrix of the geographic location preset area, the wind direction field matrix and the preset The wind direction of each sub-area in the area corresponds to the wind speed; the determining the sub-area in which the environmental state quantized value is greater than zero in the preset area includes: determining that the environmental state quantized value in the preset area is greater than zero and the wind direction is oriented Determining an orientation relationship between the sub-area in which the environmental state quantization value is greater than zero and the sub-area in which the user is located, including: determining an environmental state in the preset area The quantized value is greater than zero and the wind direction is oriented toward an orientation relationship between the sub-region of the user and the sub-region in which the user is located; the environmental state of the sub-region in which the environmental state quantized value in the preset region is greater than zero and The orientation relationship between the sub-area in which the environmental state quantization value is greater than zero and the sub-area in which the user is located in the preset area is combined into an environmental state prediction statement, including: the preset area The environmental state quantized value is greater than zero and the wind direction is toward an environmental state of the sub-region of the user, the environmental state quantized value in the preset region is greater than zero, and the wind direction is toward the sub-region of the user and the sub-region in which the user is located The orientation relationship between the two is combined into the environmental state prediction statement. The fixed-point environment state prediction method according to claim 10, wherein determining that the environmental state quantization value in the preset region is greater than zero and the wind direction is toward the sub-region of the user comprises: determining the environmental state quantization value matrix a point in which the environmental state quantized value is greater than zero, wherein a point in the environmental state quantized value matrix whose environmental state quantized value is greater than zero does not include a point corresponding to the user; and a point at which the environmental state quantized value is greater than zero is determined a first vector formed by a line connecting points corresponding to the user in the matrix of environmental state quantized values, and a second vector formed by a corresponding wind direction and wind speed of the point where the environmental state quantized value is greater than zero And determining, by the sub-region corresponding to the point that the inner product of the first vector and the second vector is greater than zero, the sub-region in which the environmental state quantization value in the preset region is greater than zero and the wind direction is toward the user. The method for predicting a fixed-point environment state according to claim 10, wherein the environmental state in the preset area is greater than zero and the wind direction is toward an environmental state of the sub-area of the user, the preset area. The medium-state state quantized value is greater than zero and the wind direction is oriented toward the orientation relationship between the sub-region of the user and the sub-region in which the user is located. Before being combined into the environmental state prediction statement, the method further includes: calculating the preset region The medium state state quantized value is greater than zero and the wind direction is toward a distance between the sub-region of the user and the sub-region in which the user is located; the environmental state quantized value in the preset region is greater than zero and the wind direction is toward the An environmental state of a sub-area of the user, an orientation state in which the environmental state quantized value in the preset area is greater than zero, and the wind direction is toward the sub-area of the user and the sub-area in which the user is located, combined into the environmental state Forecast statements, including: And an environmental state in which the environmental state quantized value in the preset area is greater than zero and the wind direction is toward the sub-area of the user, the environmental state quantized value in the preset area is greater than zero, the wind direction is toward the sub-area of the user, and the An orientation relationship between sub-regions in which the user is located, a distance between the sub-regions in which the environmental state is greater than zero, and the wind direction is toward the sub-region of the user and the sub-region in which the user is located, The environmental state forecast statement. The method for predicting a fixed-point environment state according to claim 7 further includes: generating a mapping relationship between the environmental state quantization value and the environmental state level; and using the corresponding environmental state level for the environmental state in the environmental state prediction statement. Said. The fixed-point environmental state prediction method according to claim 7, wherein the environmental state quantized value matrix comprises: a precipitation matrix, a temperature matrix, and a fine particle content matrix in the air. A fixed-point environment state prediction device includes: an acquisition module, configured to acquire geographic location information of a user and environmental state prediction data within a preset time range of the geographic location; and a processing module configured to predict data according to the environmental state Generating an environmental state prediction curve of the geographic location within the preset time range, acquiring an environmental state change point on the environmental state prediction curve, and generating an environment within the preset time range according to the environmental state change point a state prediction statement; and a sending module, configured to: push the environmental state forecast statement to the user; wherein: the processing module is configured to generate the environment state forecast data by a cubic spline interpolation method The geographical location is within the preset time range The environmental state forecast data set, the accuracy of the environmental state forecast data set in time is a preset value; and the environmental state forecast curve is generated according to the environmental state forecast data set. The device for predicting a fixed-point environment state according to claim 15 further comprising: a receiving module, configured to receive an environmental state forecast request message sent by the user. The fixed-point environmental state prediction device according to claim 15, wherein: the processing module is specifically configured to query the environmental state forecast data set, and the first-order difference absolute value of the environmental state quantization value is smaller than the first-order The differential threshold and the second-order difference absolute value are greater than the change point of the second-order differential threshold; wherein the time interval between the change point and the previous change point is greater than a preset time threshold, and the environmental state quantized value of the previous change point is greater than The change point of the preset environmental state quantization value threshold is set as the environmental state change point. The fixed-point environmental state prediction device according to any one of the items 15 to 17, wherein the processing module is specifically configured to: if there is no environmental state change point on the environmental state prediction curve, The preset time range is combined with the current environmental state as an environmental state prediction statement; if there is an environmental state change point on the environmental state prediction curve, the two points in the current time point and the environmental state change point are sequentially determined. The change trend of the environmental state between the current time point and the environmental state change trend between the two adjacent points in the environmental state change point and the time corresponding to the environmental state change point are sequentially combined into an environmental state forecast statement. The device for predicting a fixed-point environment state according to claim 18, wherein: the processing module is further configured to generate a mapping relationship between an environmental state quantization value and an environmental state level, and the environment in the environmental state prediction statement State use The corresponding environmental status level is indicated. The fixed-point environmental state prediction device according to claim 15, wherein the environmental state prediction data acquired by the acquisition module comprises: precipitation forecast data, temperature forecast data, air quality forecast data, wind direction and wind speed forecast data. A fixed-point environment state prediction device includes: an acquisition module, configured to acquire geographic location information of a user and an environmental state quantization value matrix of the geographic location preset area, the environmental state quantization value matrix and the preset area Corresponding to the environmental state quantized value of each sub-region; the processing module, configured to determine a sub-region in which the user is located in the preset region, and a corresponding point in the matrix of the environmental state quantization value of the user Determining a sub-area in which the environmental state quantized value is greater than zero in the preset area; determining an azimuth relationship between the sub-area in which the environmental state quantized value is greater than zero and the sub-area in which the user is located; The environment state of the sub-area in which the environmental state quantized value is greater than zero in the preset area and the azimuth relationship between the sub-area in which the environmental state quantized value in the preset area is greater than zero and the sub-area in which the user is located are combined into an environment a status prediction statement; and a sending module, configured to push the environmental status prediction statement to the user. The device for predicting a fixed-point environment state according to claim 21, wherein the processing module is specifically configured to calculate a sub-area in which the environmental state quantization value is greater than zero in the preset area, and where the user is located. a distance between the sub-regions; determining an orientation relationship between the sub-regions closest to the user and the sub-regions in which the user is located in the sub-regions in which the environmental state quantization value is greater than zero in the preset region. The fixed-point environmental state prediction device according to claim 21, wherein: the processing module is specifically configured to determine the environmental state quantization value moment a point in the array where the environmental state quantized value is greater than zero; determining a first vector formed by a line connecting the points corresponding to the user in the environmental state quantized value matrix at a point where the environmental state quantized value is greater than zero; A quadrant in which the vector is located determines an orientation relationship between the sub-region in which the environmental state quantization value is greater than zero and the sub-region in which the user is located. The device for predicting a fixed-point environment state according to any one of claims 21 to 23, wherein: the acquiring module is further configured to acquire a wind direction field matrix of the geographic location preset area, The wind direction field matrix corresponds to the wind direction and the wind speed of each sub-area in the preset area; the processing module is further configured to determine that the environmental state quantization value in the preset area is greater than zero and the wind direction is toward the user's child. a region; determining an orientation relationship between the environment state quantized value in the preset region greater than zero and the wind direction toward the sub-region of the user and the sub-region in which the user is located; and the environmental state quantized value in the preset region An environmental state greater than zero and a wind direction toward a sub-region of the user, an environmental state quantized value in the preset region being greater than zero, and an orientation relationship between a wind direction toward a sub-region of the user and a sub-region in which the user is located , combined into the environmental state forecast statement. The device for predicting a fixed-point environment state according to claim 24, wherein: the processing module is specifically configured to determine a point in the matrix of environmental state quantization values that is greater than zero in an environmental state quantization value, wherein the environmental state a point in the quantized value matrix whose environmental state quantized value is greater than zero does not include a point corresponding to the user; and a point at which the environmental state quantized value is greater than zero is determined in the matrix of the environmental state quantized value matrix corresponding to the point corresponding to the user a first vector formed by the line, and a second point formed by the corresponding wind direction and wind speed in the wind direction matrix in a point where the environmental state quantized value is greater than zero a sub-region corresponding to a point determining that an inner product of the first vector and the second vector is greater than zero is a sub-region in which the environmental state quantization value in the preset region is greater than zero and the wind direction is toward the user. The device for predicting a fixed-point environment state according to claim 24, wherein: the processing module is further configured to calculate a sub-region of the preset state in which the environmental state quantized value is greater than zero and the wind direction is toward the user. a distance between the sub-areas in which the user is located; an environmental state in which the environmental state quantization value in the preset area is greater than zero and the wind direction is toward the sub-area of the user, and the environmental state quantization value in the preset area is greater than Zero and wind direction toward an orientation relationship between a sub-area of the user and a sub-area in which the user is located, an environmental state quantization value in the preset area is greater than zero, and a wind direction is directed to the sub-area of the user and the user The distance between the sub-regions in which they are located is combined into the environmental state prediction statement. The device for predicting a fixed-point environment state according to claim 21, wherein: the processing module is further configured to generate a mapping relationship between an environmental state quantized value and an environmental state level, and the environment in the environmental state forecast statement The status is represented by the corresponding environmental status level. The fixed-point environmental state prediction device according to claim 21, wherein the matrix of environmental state quantized values obtained by the acquisition module comprises: a precipitation matrix, a temperature matrix, and a matrix of fine particle content in the air.