CN108318942A - Weather prediction method and weather forecasting device - Google Patents
Weather prediction method and weather forecasting device Download PDFInfo
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- CN108318942A CN108318942A CN201810170874.XA CN201810170874A CN108318942A CN 108318942 A CN108318942 A CN 108318942A CN 201810170874 A CN201810170874 A CN 201810170874A CN 108318942 A CN108318942 A CN 108318942A
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- G01W—METEOROLOGY
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Abstract
The present invention provides a kind of weather prediction method, including：Multiple users are obtained for the feedback of weather conditions and the position of the multiple user and the time of feedback；According to the time of the space length and the multiple user feedback in the position of the multiple user and a precalculated position and the duration of a predetermined time separately, the confidence level of the feedback of the multiple user is calculated；According to the confidence level of the feedback of the multiple user, the weather conditions in the precalculated position are calculated.
Description
Technical field
The present invention relates to weather field more particularly to a kind of weather prediction method and weather forecasting devices.
Background technology
For Short-term Forecast, different places per minute can all receive many user feedback datas, and feedback data, which can be divided into, to be had
Rain and without two class of rain.For various reasons, however not excluded that field feedback is error message, for example user accidentally touches, user network
Delay is not intended to or feedback error weather etc. intentionally, therefore directly can not carry out true weather at this time by user feedback data
Judge.
Under existing technical support, it is very accurate that data of weather forecast can not be accomplished, it is accurate to improve data of weather forecast
The good mode of true rate is the support of user data.User feedback data have real-time is high, fineness is high, accuracy compared with
High advantage can substantially calculate the weather condition in a region by the data of user feedback.But due to user feedback number
According to Mass Distribution unevenness, need to calculate the confidence level of user feedback data.
For general user feedback confidence calculations, centainly a rule chooses user feedback for usually manual setting
As a result.For example user feedback is most in certain space-time unique weather phenomenon is chosen as a result, to each user feedback
A weighting processing is done, it is maximum as a result to choose result.
The technology contents listed in the prior art only represent the technology that inventor is grasped, and are not considered naturally
It is the prior art and is used to evaluate the novelty and creativeness of the present invention.
Invention content
The object of the invention on the basis of user feedback data, builds Bayesian model, estimates according to knowledge of statistics
In a certain range, in certain time user feedback data confidence level, you can it is certain a kind of probability to be inferred to true weather,
True weather at this time is may determine that by probability stool and urine.
The present invention has chosen a kind of mode based on Bayesian model in probability statistics, fully considered user feedback when
Between, influence of the space to the user feedback data weights, have preferable principle and accuracy.By the model user feedback institute
Calculated weather information accuracy rate is up to 90%.
The present invention provides a kind of weather prediction method, including：Multiple users are obtained for the feedback of weather conditions and institute
State the position of multiple users and the time of feedback；According to the space length of the position of the multiple user and a precalculated position, with
And the time of the multiple user feedback and the duration of a predetermined time separately, calculate the confidence of the feedback of the multiple user
Degree；According to the confidence level of the feedback of the multiple user, the weather conditions in the precalculated position are calculated.
According to an aspect of the present invention, the confidence level of the feedback of the multiple user is calculated using following formula：
Wherein, x and y is the space length of the position and the precalculated position of the user, and t is the multiple user feedback
Time and the duration of the predetermined time separately, k is predetermined coefficient, and k is preferably determined so that when user is in distance
Confidence level when 20 minutes current times, current location radius are equal to 20 kilometers is 0.5.
According to an aspect of the present invention, the weather conditions in the precalculated position are predicted using Bayesian model.
According to an aspect of the present invention, the weather conditions include rainy and without rain.
According to an aspect of the present invention, further include：It is higher than the user feedback of certain threshold value for confidence level, notifies the use
The corresponding user of family feedback.
According to an aspect of the present invention, the weather prediction method further includes：Day according to the precalculated position is vaporous
Condition, modification forecast.According to user feedback data, time update live data in short-term corrects Short-term Forecast input data source, with reality
Now correct the effect of Short-term Forecast.
According to an aspect of the present invention, before calculating the confidence level of feedback of the multiple user, distance is filtered out
The precalculated position is more than predetermined spatial distance and/or the user feedback apart from the predetermined time more than scheduled duration.
The invention further relates to a kind of weather forecasting devices, including：User feedback acquiring unit is configured to obtain multiple users
Feedback and the position of the multiple user for weather conditions and the time of feedback；User feedback confidence computation unit,
It is configured to the time according to the position of the multiple user and the space length in a precalculated position and the multiple user feedback
With the duration of a predetermined time separately, the confidence level of the feedback of the multiple user is calculated；Weather conditions computing unit, according to
The confidence level of the feedback of the multiple user calculates the weather conditions in the precalculated position.
The invention further relates to a kind of computer readable storage mediums, including the computer executable instructions being stored thereon,
The executable instruction implements weather prediction method as described above when being executed by processor.
Description of the drawings
Attached drawing is used to provide further understanding of the present invention, and a part for constitution instruction, the reality with the present invention
It applies example to be used to explain the present invention together, not be construed as limiting the invention.In the accompanying drawings：
Fig. 1 is the schematic diagram of weather prediction method according to an embodiment of the invention；
Fig. 2 is user feedback sample space schematic diagram according to an embodiment of the invention；
Fig. 3 is the schematic diagram of weather forecasting device according to an embodiment of the invention；
Fig. 4 is the block diagram of the computer program product of at least some embodiment arrangements according to the present invention.
Specific implementation mode
Hereinafter, certain exemplary embodiments are simply just described.As one skilled in the art will recognize that
Like that, without departing from the spirit or scope of the present invention, described embodiment can be changed by various different modes.
Therefore, attached drawing and description are considered essentially illustrative rather than restrictive.
In the description of the present invention, it is to be understood that, term " width ", " upper ", " under ", " interior ", " outer " equal instructions
Orientation or positional relationship is to be based on the orientation or positional relationship shown in the drawings, and is merely for convenience of the description present invention and simplification is retouched
It states, does not indicate or imply the indicated device or element must have a particular orientation, with specific azimuth configuration and operation,
Therefore it is not considered as limiting the invention.In addition, term " first ", " second " are used for description purposes only, and cannot understand
To indicate or implying relative importance or implicitly indicate the quantity of indicated technical characteristic.Define as a result, " first ", "
Second " feature can explicitly or implicitly include one or more feature.
In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, term " connected " " connects
It connects and " shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or be integrally connected:It can be machine
Tool connects, and can also be to be electrically connected or can mutually communicate；It can be directly connected, the indirect phase of intermediary can also be passed through
Even, can be the interaction relationship of the connection or two elements inside two elements.For those of ordinary skill in the art
For, the specific meanings of the above terms in the present invention can be understood according to specific conditions.
In the present invention unless specifically defined or limited otherwise, fisrt feature second feature its " upper " or it " under "
It may include that the first and second features are in direct contact, can also not be to be in direct contact but pass through it including the first and second features
Between other characterisation contact.Moreover, fisrt feature second feature " on ", " top " and " above " include first spy
Sign is right over second feature and oblique upper, or is merely representative of fisrt feature level height and is higher than second feature.Fisrt feature exists
Second feature " under ", " lower section " and it is " following " including fisrt feature right over second feature and oblique upper, or be merely representative of
Fisrt feature level height is less than second feature.
Following disclosure provides many different embodiments or example is used for realizing the different structure of the present invention.In order to
Simplify disclosure of the invention, hereinafter the component of specific examples and setting are described.Certainly, they are merely examples, and
And it is not intended to limit the present invention.In addition, the present invention can in different examples repeat reference numerals and/or reference letter,
This repetition is for purposes of simplicity and clarity, itself not indicate between discussed various embodiments and/or setting
Relationship.In addition, the present invention provides various specific techniques and material example, but those of ordinary skill in the art can be with
Recognize the application of other techniques and/or the use of other materials.
The preferred embodiment of the present invention is illustrated below in conjunction with attached drawing, it should be understood that described herein preferred
Embodiment is only for the purpose of illustrating and explaining the present invention and is not intended to limit the present invention.
Fig. 1 shows weather prediction method 100 according to an embodiment of the invention.It should below with reference to Fig. 1 detailed descriptions
Weather prediction method 100.
In step S101, obtain multiple users for the feedback of weather conditions and the position of the multiple user feedback and
Time.The feedback of the user is for example including user for the report of weather conditions at that time, such as rainy, snowfall, sunny, mist
Haze, hail etc..The present invention is not limited to the types of specific weather conditions.Those of ordinary skill is it is understood that implementing this hair
When bright, under the teachings of the present invention and enlightenment, it can increase or reduce specific weather conditions type, such as weather conditions can
Only to include precipitation and non-precipitation two types.These are all within the scope of the present invention.In general, user can be mobile whole
User feedback is submitted in APP on such as mobile phone of end.When cell phone application submits the user feedback to server, while can incite somebody to action
The information such as geographical location, submission feedback time residing for the user submit to server simultaneously.Geographical location for example can come from
Position indicated by the terminal GPS of user, can also be when user is using the wireless networks such as 4G, 3G, GSM, GPRS, WLAN,
According to its IP address either mobile communication base station or user information and determination position, can also be when user is using wired
According to position determined by its IP address when network.
In step S102, according to the space length in the position of the multiple user and a precalculated position and the multiple
The time of user feedback and the duration of a predetermined time separately, calculate multiple confidence levels of the feedback of the multiple user.
Using the precalculated position and predetermined time as space-time central point, it is assumed that put surrounding 20Km centered on the space-time unique of selection
Interior, all user feedbacks within 20 minutes predetermined times are sample space, and the user for being located at the space-time unique edge is anti-
The initial confidence level of feedback is 0.5, and for being located at the user that distance center point is (x, y, t), (wherein x, y are space length, and t is
Time gap), initial confidence level can be calculated according to following formula：
In above formula, k is the coefficient manually set.From formula as can be seen that the initial confidence level of user feedback is with user
Increase with a distance from central point and gradually decay, finally decays to edge confidence degree 0.5 and (by taking precipitation and without precipitation as an example, respectively account for
50% possibility).
As shown in Fig. 2, in the sample space of multiple user feedbacks, X-axis and Y-axis are indicated apart from the precalculated position (origin O)
Horizontal and vertical coordinate, T axis indicates preset distance time point duration separately.
In other words, the user feedback that distance center point is closer, the preset distance time is closer, confidence level are higher.According to
One embodiment of the present of invention, the predetermined time are, for example, current time, one before or after can also be current time
Time point.It is assumed that for some place sometime, closer user feedback is more credible with a distance from the point, when from this
It is more credible to carve the shorter user feedback of time interval, then for each user feedback, user feedback can be passed through
Time interval length, space length distance COMPREHENSIVE CALCULATING go out the confidence of each user feedback under the weather phenomenon of there and then
Degree, as shown in Figure 2.
In addition, the weather prediction method in the present invention, is not limited to the prediction for future weather conditions or forecast,
Also include the prediction for past a certain moment weather.
The precalculated position is calculated described predetermined according to the confidence level of the feedback of the multiple user in step S103
The weather conditions of time.
According to a preferred embodiment of the present invention, the precalculated position can be calculated according to Bayesian model described
The weather conditions of predetermined time.Bayesian model is a classical model in probability theory.Bayesian inference is Bayesian formula
A kind of application.Bayesian formula is as follows：
Bayesian inference (BAYES IAN INFERENCE) is a kind of statistics applied to the decision under condition of uncertainty
Method.Bayesian inference is noteworthy characterized by, and a statistical conclusions can utilize prior information and sample information in order to obtain,
(in this model, prior information is that the probability to rain in the case of completely without other information is 0.5, sample information, that is, every
The confidence level of a user feedback).Deduction is the conclusion obtained based on phenomenon or the decision made.Statistical inference is based on real generation
The conclusion of the not observable attribute in the related world, commonly known as hypothesis testing obtained from the feature that boundary observes.It is counting
In, the feature of observable is not often referred to as parameter, and the feature observed then is referred to as data or sample information.Bayes
Statistical inference is to allow investigator not only to use sample information in such a way that logic is consistent when assessing statistical hypothesis but also use priori
A kind of method of information.
According to one embodiment of present invention, the prior probability of each weather phenomenon is set as being consistent, it is all
The user feedback in the region constitutes sample space, by using Bayes principle to these samples, can calculate the area
The confidence level of certain weather phenomenon of domain, the highest weather phenomenon of confidence level are the weather phenomenon in this time of the region.One
A calculated examples are as follows：Assuming that in a space-time unique, there are three user feedbacks altogether, are calculated according to respective time-space matrix
Confidence level be respectively p (B1 | A1)=0.6, p (B2 | A1)=0.7, p (B3 | A1)=0.8, p (A1)=0.5, wherein B1, B2
It is respectively user feedback with B3, A1 is precipitation event, substitutes into the probability that above-mentioned Bayesian formula can be obtained p (A1 | B), that is, exists
The probability to rain under conditions of the user feedback.According to one embodiment of present invention, the weather phenomenon comprise only rain and
Without rain.
Detailed calculating process is as follows：
It assumes initially that：P (A) rains for event, and P (B) is all user feedback events spaces, is had according to Bayesian formula：
There is abbreviation at two in above-mentioned formula and converts as follows：
It is assumed that in the case of rainy feed back rain and fed back in the case of no rain rainy confidence level and be 1,
The case where without rain, is same.
According to one embodiment of present invention, in the probability of calculated various weather phenomena according to Bayesian formula,
The highest weather phenomenon of probability, the weather conditions of the as described precalculated position at the time point.By taking rain, without rain as an example, counting
After the confidence level for calculating multiple user feedbacks, the confidence level is inputted into Bayesian formula, at the same it is rainy, the priori without rain is general
Rate is for example 50%, and it is 85% to calculate rainy probability, and the probability of no rain is 15%.Then the precalculated position is in the time
The weather of point is rain.
According to one embodiment of present invention, for the user feedback consistent with the calculated weather phenomenon, notice
User corresponding to the user feedback.
It according to one embodiment of present invention, will after obtaining the weather conditions of the precalculated position at the time point
The weather conditions are input in weather forecast system, carry out the prediction of future weather conditions.The weather forecast system is, for example,
Nowcasting system, nowcasting system are the systems of the following two hours two kilometers of lattice point precipitation events per minute of a forecast,
Main input is radar return data, city live data and user feedback data.Since identified weather conditions are most smart
True, consider the feedback of user and the confidence level of user feedback, thus, the essence of the prediction of the future weather conditions
Degree and accuracy can be improved.Therefore, computational methods are accepted and believed in user feedback data and the user feedback, to entirely pre- in short-term
Reporting system plays an important role.
According to one embodiment of present invention, before calculating the confidence level of feedback of the multiple user, filter out away from
From the precalculated position be more than predetermined spatial distance and/or with a distance from the predetermined time be more than scheduled duration user feedback.Cause
For the user feedback provided in the position with the precalculated position hypertelorism, and/or with the predetermined time apart from excessive
The user feedback that provides of time point may not for the precalculated position in the assessment of the weather conditions of the predetermined time
With big reference value.Therefore it is filtered out in advance.
In the present invention, Bayesian inference is applied in user feedback system, acquires user feedback data, it is anti-using user
Present supplementary function of the data to weather data so that weather data is much sooner, accurately.
The inference problems of the true weather of user feedback are solved using Bayesian model, and Short-term Forecast, experience are optimized with this
Card is a very effective method.The model perfectly meets following three objective requirements：
(1) nearby there is more more user feedbacks unanimously fed back are easier to be accepted and believed
(2) the closer user feedback of space length is easier is accepted and believed
(3) user feedback closer on the time is easier is accepted and believed
In practical applications, which solves the drawbacks of Short-term Forecast is by radar station data, has enough users anti-
When feedback amount, have great importance for the accuracy and actual effect of Short-term Forecast.Radar data there are some objective problems, than
If radar noise either close therefore the case where can cause to report by mistake or fail to report by radar station, user feedback data is with another number
This deficiency is compensated for according to mode.
Fig. 3 shows a kind of weather forecasting device 300 in accordance with another embodiment of the present invention.It is described below in detail described
Weather forecasting device 300.
As shown in figure 3, the weather forecasting device 300 includes：User feedback acquiring unit 301 is configured to obtain multiple
User is for the feedback of weather conditions and the position of the multiple user and the time of feedback；User feedback confidence calculations list
Member 302, is configured to according to the position of the multiple user and the space length in a precalculated position and the multiple user feedback
Time and the duration of a predetermined time separately, calculate the confidence level of the feedback of the multiple user；Weather conditions calculate single
Member 303, according to the confidence level of the feedback of the multiple user, calculates the weather conditions in the precalculated position.
Fig. 4 is the block diagram according to the computer program product 500 of at least some embodiments arrangement of the present invention.Signaling bearer
Medium 502 may be implemented as or be situated between including computer-readable medium 506, computer recordable media 508, computer communication
Matter 510 or combination thereof, storage configurable processing unit with execute be previously described during all or some
Programming instruction 504.These instructions may include for example for making one or more processors execute one or more handled as follows
A executable instruction：Obtain multiple users for the feedback of weather conditions and the position of the multiple user and feedback when
Between；According to the time of the space length in the position of the multiple user and a precalculated position and the multiple user feedback with
The duration of one predetermined time separately, calculates the confidence level of the feedback of the multiple user；According to the feedback of the multiple user
Confidence level, calculate the precalculated position the predetermined time weather conditions.
Although the detailed description of front elaborates device and/or mistake by block diagram, flow chart and/or exemplary use
Each example of journey, but such block diagram, flow chart and/or example include one or more functions and/or operation, this field
The skilled person will understand that can by various hardware, software, firmware or almost its arbitrary combination come individually
And/or uniformly realize each function in such block diagram, flow chart or example and/or operation.In one example, herein
If the stem portion of described theme can be believed via application-specific integrated circuit (ASIC), field programmable gate array (FPGA), number
Number processor (DSP) or other integrated forms are realized.However, it will be understood by those skilled in the art that disclosed herein show
Example some aspects wholly or partly can equally be realized in integrated circuits, be embodied as one or more calculate
The one or more computer programs run on machine are (for example, be embodied as run in one or more computer systems one
Or multiple programs), one or more programs for being embodied as running on the one or more processors are (for example, be embodied as at one
Or the one or more programs run on multi-microprocessor), be embodied as firmware or be embodied as above substantially any combination,
And according to content of this disclosure, for the software and/or firmware design circuit and/or write code will be in art technology
Within the scope of the technical ability of personnel.For example, if user judge speed and precision it is important, user can select main hardware and/
Or firmware vehicle；If flexibility is important, user can select major software embodiment；Alternatively, additionally optionally, making
User can select certain combination of hardware, software and/or firmware.
In addition, it will be appreciated by those skilled in the art that the mechanism of subject matter described herein can be used as various forms
Program product be distributed, and regardless of be practically used for implement distribution signal bearing medium concrete type, herein
The illustrated examples of described theme are all suitable for.The example of signal bearing medium includes but not limited to following：Recordable type is situated between
Matter, floppy disk, hard disk drive, compact disk (CD), digital video disc (DVD), number tape, computer storage etc.；And
Transmission type media, such as number and/or analogue communication medium are (for example, optical fiber cable, waveguide, wired communications links, wireless communication
Link etc.).
It will be appreciated by those skilled in the art that commonly describing device in a manner of set forth herein in the art
And/or process, hereafter utilizing works practice will be in the device that described in this way and/or process integration to data processing system.That is,
At least part of apparatus described herein and/or process can be integrated into data processing system by the experiment of reasonable amount
In.It will be appreciated by those skilled in the art that one or more during typically data processing system generally includes as follows：System
Unit housings, video display devices, such as memory of volatile and non-volatile memory, such as microprocessor and number letter
Number processor of processor, the computational entity of such as operating system, driver, graphical user interface and application program are such as touched
One or more interactive devices of template or touch screen, and/or including feedback loop and control motor (for example, for sensing position
It sets and/or the feedback of speed；Control motor for moving and/or adjusting component and/or amount) control system.Typically
Data processing system can be realized using any suitable commercially available component, such as data calculating communication and/or network calculations/
Common component in communication system.
Finally it should be noted that：The foregoing is only a preferred embodiment of the present invention, is not intended to restrict the invention,
Although the present invention is described in detail referring to the foregoing embodiments, for those skilled in the art, still may be used
With technical scheme described in the above embodiments is modified or equivalent replacement of some of the technical features.
All within the spirits and principles of the present invention, any modification, equivalent replacement, improvement and so on should be included in the present invention's
Within protection domain.
Claims (9)
1. a kind of weather prediction method, including：
Multiple users are obtained for the feedback of weather conditions and the position of the multiple user and the time of feedback；
According to the time of the space length in the position of the multiple user and a precalculated position and the multiple user feedback with
The duration of one predetermined time separately, calculates the confidence level of the feedback of the multiple user；
According to the confidence level of the feedback of the multiple user, calculate the precalculated position the predetermined time weather conditions.
2. weather prediction method according to claim 1, which is characterized in that calculate the multiple user using following formula
Feedback confidence level：
Wherein, x and y be the user position and the precalculated position space length, t for the multiple user feedback when
Between duration with the predetermined time separately, k is predetermined coefficient, and k is preferably determined so that when to be in distance current by user
Confidence level when 20 minutes moment, current location radius are equal to 20 kilometers is 0.5.
3. weather prediction method according to claim 1 or 2, which is characterized in that predicted using Bayesian model described pre-
The weather conditions in the predetermined time are set in positioning.
4. weather prediction method according to any one of claim 1-3, which is characterized in that the weather conditions include
Rain and without rain.
5. according to the weather prediction method described in any one of claim 1-4, which is characterized in that further include：For confidence level
Higher than the user feedback of certain threshold value, the user corresponding to the user feedback is notified.
6. weather prediction method according to any one of claims 1-5, which is characterized in that further include：According to described pre-
Position the weather conditions set, modification forecast.According to user feedback data, time update live data in short-term corrects Short-term Forecast
Input data source, to realize the effect for correcting Short-term Forecast.
7. according to the weather prediction method described in any one of claim 1-6, which is characterized in that calculating the multiple user
Feedback confidence level before, it is more than predetermined spatial distance and/or apart from the pre- timing to filter out apart from the precalculated position
Between be more than scheduled duration user feedback.
8. a kind of weather forecasting device, including：
User feedback acquiring unit is configured to obtain multiple users for the feedback of weather conditions and the position of the multiple user
The time set and fed back；
User feedback confidence computation unit, be configured to according to the space in the position of the multiple user and a precalculated position away from
From and the multiple user feedback time and the duration of a predetermined time separately, calculate the feedback of the multiple user
Confidence level；
Weather conditions computing unit calculates the precalculated position described pre- according to the confidence level of the feedback of the multiple user
The weather conditions fixed time.
9. a kind of computer readable storage medium, including the computer executable instructions that are stored thereon, the executable instruction
Implement the weather prediction method as described in any one of claim 1-7 when being executed by processor.
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| CN201810170874.XA CN108318942A (en) | 2018-03-01 | 2018-03-01 | Weather prediction method and weather forecasting device |
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Cited By (1)
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| CN111835832A (en) * | 2020-06-16 | 2020-10-27 | 上海掌门科技有限公司 | Method and equipment for providing weather notification information |
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