CN117593871A

CN117593871A - Typhoon influence prediction method, typhoon influence prediction device, electronic equipment and storage medium

Info

Publication number: CN117593871A
Application number: CN202311552968.0A
Authority: CN
Inventors: 李晓彬; 詹丹丹; 邓丽娟; 郑立华; 李旺军
Original assignee: China Southern Power Grid Digital Platform Technology Guangdong Co ltd
Current assignee: China Southern Power Grid Digital Platform Technology Guangdong Co ltd
Priority date: 2023-11-20
Filing date: 2023-11-20
Publication date: 2024-02-23

Abstract

The invention discloses a typhoon influence prediction method, a typhoon influence prediction device, electronic equipment and a storage medium. The typhoon influence prediction method comprises the following steps: obtaining path forecast data corresponding to a target typhoon, and determining a first time interval according to the path forecast data, wherein the first time interval is a time interval in which the target typhoon affects a target area; determining a second time interval based on the first time interval, wherein the second time interval is an intersection of a predicted time period and the first time interval; and acquiring numerical forecasting data corresponding to the target typhoon based on the path forecasting data, and determining an influence forecasting result of the target typhoon on the target area in the second time interval based on the numerical forecasting data. Based on the technical scheme of the embodiment of the invention, the efficiency and the accuracy of typhoon influence prediction can be improved.

Description

Typhoon influence prediction method, typhoon influence prediction device, electronic equipment and storage medium

Technical Field

The present invention relates to the field of computer application technologies, and in particular, to a typhoon influence prediction method, apparatus, electronic device, and storage medium.

Background

For the power system, typhoons come on, the influence of shortening the service life of a wind generating set, seriously damaging blades, overturning a tower, damaging a power grid transmission line and the like can be caused, and even the whole power system can be paralyzed. Therefore, the related art generally predicts the influence of typhoons to prepare precautions to ensure stable operation of the power system.

It will be appreciated that there are a variety of products for typhoons forecasts and that a variety of products may be obtained directly. But each product has advantages and disadvantages and has inconsistent and incompatible problems. In the related art, products corresponding to the predicted demand are generally obtained according to the predicted demand, and then typhoon influence prediction is performed based on the obtained products, for example, in the case that the demand is high-precision prediction, numerical prediction products are obtained for prediction; under the condition that the demand is high update frequency prediction, a path prediction product is obtained for prediction, so that a typhoon influence prediction method which simultaneously meets high efficiency and high accuracy is lacking at present.

Disclosure of Invention

The invention provides a typhoon influence prediction method, a typhoon influence prediction device, electronic equipment and a storage medium, which are used for solving the technical problem of lack of the typhoon influence prediction method capable of simultaneously meeting high efficiency and high accuracy.

According to an aspect of the present invention, there is provided a typhoon influence prediction method, wherein the method includes:

obtaining path forecast data corresponding to a target typhoon, and determining a first time interval according to the path forecast data, wherein the first time interval is a time interval in which the target typhoon affects a target area;

determining a second time interval based on the first time interval, wherein the second time interval is an intersection of a predicted time period and the first time interval;

and acquiring numerical forecasting data corresponding to the target typhoon based on the path forecasting data, and determining an influence forecasting result of the target typhoon on the target area in the second time interval based on the numerical forecasting data. According to another aspect of the present invention, there is provided a typhoon influence prediction apparatus, wherein the apparatus includes:

the data acquisition module is used for acquiring path forecast data corresponding to a target typhoon, and determining a first time interval according to the path forecast data, wherein the first time interval is a time interval in which the target typhoon affects a target area;

a time determining module, configured to determine a second time interval based on the first time interval, where the second time interval is an intersection of a predicted time period and the first time interval;

And the influence prediction module is used for acquiring numerical prediction data corresponding to the target typhoon based on the path prediction data, and determining an influence prediction result of the target typhoon on the target area in the second time interval based on the numerical prediction data.

According to another aspect of the present invention, there is provided an electronic apparatus including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the typhoon impact prediction method according to any one of the embodiments of the present invention.

According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to implement the typhoon impact prediction method according to any one of the embodiments of the present invention when executed.

According to the technical scheme, the first time interval is determined according to the path forecast data by acquiring the path forecast data corresponding to the target typhoon, wherein the first time interval is the time interval of the target typhoon affecting the target area; determining a second time interval based on the first time interval, wherein the second time interval is an intersection of a predicted time period and the first time interval; and acquiring numerical forecasting data corresponding to the target typhoon based on the path forecasting data, and determining an influence forecasting result of the target typhoon on the target area in the second time interval based on the numerical forecasting data. According to the technical scheme, typhoon forecast data (namely path forecast data and numerical forecast data) of two different types, different formats, different timeliness, different update frequencies and different forecast contents can be effectively fused, so that influence of target typhoons on a target area in a concerned time interval is forecast, the problem that the path forecast data and the numerical forecast data are incompatible is solved, and the efficiency and the accuracy of typhoon influence forecast are improved.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flowchart of a typhoon impact prediction method according to a first embodiment of the present invention;

FIG. 2 is a scene graph of path forecast data provided in accordance with an embodiment of the present invention;

FIG. 3 is a scene graph of numerical forecast data provided in accordance with an embodiment of the present invention;

fig. 4 is a flowchart of a typhoon influence prediction method according to a second embodiment of the present invention;

FIG. 5 is a scene graph of a correspondence between characterization path forecast data and numerical forecast data, provided in accordance with an embodiment of the present invention;

FIG. 6 is an overall flowchart of a typhoon impact prediction method provided according to an embodiment of the present invention;

FIG. 7 is an overall algorithm flow chart of a typhoon impact prediction method provided according to an embodiment of the present invention;

fig. 8 is a schematic structural view of a typhoon influence prediction apparatus according to a third embodiment of the present invention;

fig. 9 is a schematic structural diagram of an electronic device implementing a typhoon influence prediction method according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example 1

Fig. 1 is a flowchart of a typhoon effect prediction method according to an embodiment of the present invention, where the method may be implemented by a typhoon effect prediction device, and the typhoon effect prediction device may be implemented in hardware and/or software, and the typhoon effect prediction device may be configured in a computer. As shown in fig. 1, the method includes:

s110, obtaining path forecast data corresponding to a target typhoon, and determining a first time interval according to the path forecast data, wherein the first time interval is a time interval in which the target typhoon affects a target area.

The target typhoons may be understood as typhoons that may have a safety effect on a target area. In the embodiment of the present invention, the target typhoon may be specifically set according to the scene requirement, which is not specifically limited herein. Alternatively, the target typhoons may be one or more.

The path forecast data may be understood as data updated in real time characterizing the path characteristics of the target typhoons. Optionally, the path forecast data may include a plurality of path forecast points corresponding to the target typhoon, and longitude and latitude coordinates and forecast time corresponding to each of the path forecast points. Wherein the path forecast point may be understood as a forecast point (refer to fig. 2) characterizing a central forward route of the target typhoon, wherein fig. 2 is a scene graph of path forecast data provided according to an embodiment of the present invention. The path forecast data includes a plurality of path forecast points. Optionally, the path forecast data further includes central wind power information corresponding to each path forecast point. The longitude and latitude coordinates can be understood as the coordinates of the longitude and latitude corresponding to each path forecast point. The forecasted time may be understood as the time when the forecasted target typhoon reaches the current path forecast point. Alternatively, the forecast time may be a point in time.

The first time interval may be understood as a time interval in which the target typhoon affects a target area. Wherein the target area may be understood as an area of interest for typhoons affecting prediction. In the embodiment of the present invention, the target area may be preset according to a scene requirement, which is not specifically limited herein. Alternatively, the target area may be a plain of a certain area, a basin or mountain area, or the like.

S120, determining a second time interval based on the first time interval, wherein the second time interval is an intersection of the predicted time period and the first time interval.

Wherein the second time interval may be understood as a time interval during which the target typhoon affects the target area within the predicted time period.

Wherein the prediction period may be understood as a period of time of interest for which typhoons affect prediction. In the embodiment of the present invention, the prediction period may be preset according to the scene requirement, which is not specifically limited herein. Alternatively, the prediction period may be 24h, 48h, 72h, or the like.

Optionally, the determining a second time interval based on the first time interval includes:

and acquiring a real-time point, and acquiring an intersection of the predicted time period and the first time interval by taking the current real-time point as a starting point to serve as the second time interval.

Illustratively, in the case that the predicted time period is 72h, an intersection of the time period of 72h in the future and the first time interval is obtained as the second time interval, starting from the current time.

S130, acquiring numerical prediction data corresponding to the target typhoon based on the path prediction data, and determining an influence prediction result of the target typhoon on the target area in the second time interval based on the numerical prediction data.

The numerical forecast data may be understood as numerical data (refer to fig. 3) for forecasting the influence degree of the target typhoon on each sub-region in the target region, where fig. 3 is a scene diagram of the numerical forecast data according to an embodiment of the present invention.

Optionally, the numerical forecast data may include wind farm forecast data and/or rainfall forecast data. The wind field forecast data can be understood as forecast numerical data representing the influence degree of the target typhoon on the wind field of each subarea in the target area. The rainfall forecast data may be understood as numerical data for forecasting the extent of rainfall impact of the target typhoons on each sub-region in the target region.

The influence prediction result may be understood as a predicted influence result of the target typhoon on the target area in the second time interval.

Optionally, the influence prediction result may include a target early-warning area and a target early-warning level corresponding to each target early-warning area.

The target early warning area can be understood as an area needing early warning and having typhoon influence risk. The target pre-warning area may be all or part of the target area, and the target area may include one or more of the target pre-warning areas.

The target early warning level can be understood as an early warning level corresponding to each target early warning area. In the embodiment of the invention, the target early warning levels corresponding to different target early warning areas can be the same or different.

Optionally, the typhoon influence prediction method further includes:

and determining early warning equipment in the target area based on the influence prediction result, and carrying out risk early warning on the early warning equipment.

The early warning device can be understood as a device which needs to perform early warning. Alternatively, the early warning device may be a device predicted to be likely to be affected by the target typhoon based on the influence prediction result. In the embodiment of the present invention, the early warning device may be preset according to the scene requirement, which is not specifically limited herein. Alternatively, the early warning device may be an electrical device.

The risk early warning may be understood as an early warning operation for the early warning device. In the embodiment of the present invention, the risk early warning operation may be preset according to the scene requirement, which is not specifically limited herein. Optionally, the risk early warning operation may be a speaker early warning device and/or a light emitting early warning device.

Example two

Fig. 4 is a flowchart of a typhoon influence prediction method according to a second embodiment of the present invention, where the second time interval is determined based on the first time interval in the foregoing embodiment. As shown in fig. 4, the method includes:

s210, obtaining path forecast data corresponding to the target typhoons.

Optionally, the path forecast data includes a plurality of path forecast points, longitude and latitude coordinates and forecast time corresponding to each path forecast point, and the target area includes at least one path forecast point.

S220, determining longitude and latitude coordinates of each path forecasting point in the path forecasting data.

S230, determining the path forecasting point in the target area based on the longitude and latitude coordinates, and determining the first time interval based on the current path forecasting point and the forecasting time corresponding to the current path forecasting point.

In the embodiment of the present invention, each of the path forecast points corresponds to one of the longitude and latitude coordinates, and each of the path forecast points corresponds to one of the forecast times.

Wherein the current path forecast point may be understood as the path forecast point within the target area. In an embodiment of the present invention, the current path forecast point may include one or more.

In case there are a plurality of the currently described path forecast points. Optionally, determining the first time interval based on the current path forecast point and the forecast time corresponding to the current path forecast point includes:

determining the forecast time corresponding to each current path forecast point, and determining candidate time periods among the forecast times;

and taking the largest time period in the candidate time periods as the first time interval.

S240, determining a second time interval based on the first time interval.

S250, acquiring numerical prediction data corresponding to the target typhoon based on the path prediction data, and determining an influence prediction result of the target typhoon on the target area in the second time interval based on the numerical prediction data.

Optionally, the obtaining the numerical forecast data corresponding to the target typhoon based on the path forecast data includes:

and determining the forecasting time of each path forecasting point in the target area, and acquiring the numerical forecasting data corresponding to each path forecasting point based on the forecasting time.

According to the technical scheme, the forecasting time of each path forecasting point in the target area is determined, and the numerical forecasting data corresponding to each path forecasting point are obtained based on the forecasting time. The method solves the problem that the path forecast data and the numerical forecast data are not compatible, and realizes the compatibility of the path forecast data and the numerical forecast data.

Optionally, the numerical forecast data includes a numerical forecast time. The numerical forecasting time can be understood as the forecasting time corresponding to the numerical forecasting data. It will be appreciated that the numerical forecast data may be different for different of the numerical forecast times for the same of the path forecast points.

In the embodiment of the present invention, for each of the path forecast points, the forecast time is the same as the numerical forecast time (refer to fig. 5), where fig. 5 is a scene graph representing a correspondence between path forecast data and numerical forecast data provided in accordance with the embodiment of the present invention.

Specifically, for each of the path forecast points in the current path forecast data, determining the forecast time; determining the numerical forecast time based on the forecast time; and obtaining the numerical forecast data corresponding to the current path forecast point based on the numerical forecast time.

Optionally, the determining, based on the numerical forecast data, a predicted result of the influence of the target typhoon on the target area in the second time interval includes:

and determining an influence prediction result of the target typhoon on each path prediction point in the target area in the second time interval based on the numerical prediction data, wherein the influence prediction result comprises at least one target early-warning area corresponding to each path prediction point and a target early-warning grade corresponding to each target early-warning area.

Optionally, the target early-warning area may include a wind field early-warning area and/or a rainfall early-warning area.

The target early warning level may include a wind park early warning level and/or the rainfall early warning level.

According to the technical scheme provided by the embodiment of the invention, the influence prediction result of the target typhoon on each path prediction point in the target area in the second time interval is determined based on the numerical prediction data, so that the accuracy of the determined influence prediction result is improved.

Optionally, the numerical prediction data includes wind field prediction data and/or rainfall prediction data, and the determining, based on the numerical prediction data, an effect prediction result of the target typhoon on each path prediction point in the target area in the second time interval includes:

based on the wind field forecast data and the rainfall forecast data, respectively determining a wind field influence result and a rainfall influence result of the target typhoon on each path forecast point in the target area in the second time interval;

the influence prediction result is determined based on the wind field influence result and the rainfall influence result.

The wind field forecast data may be understood as forecast data representing the degree of influence of the target typhoon on the wind field of each sub-region in the target region.

The rainfall forecast data may be understood as forecast data characterizing the extent of rainfall impact of the target typhoons on each sub-region in the target area.

The wind field impact result may be understood as a predicted impact result of the wind field of the target typhoon on the target area in the second time interval.

The rainfall impact result may be understood as a predicted impact result of rainfall of the target typhoon on the target area in the second time interval.

Optionally, the wind field influence result comprises at least one wind field early warning area and a wind field early warning grade corresponding to each wind field early warning area, the rainfall influence result comprises at least one rainfall early warning area and a rainfall early warning grade corresponding to each rainfall early warning area,

the determining the influence prediction result based on the wind farm influence result and the rainfall influence result includes:

determining the target early warning area based on the wind field early warning area and/or the rainfall early warning area;

and determining a target early-warning level corresponding to the target early-warning area based on the wind field early-warning level and/or the rainfall early-warning level.

The wind field early warning area can be understood as an area needing early warning and having wind field influence risks. The wind field pre-warning area may be all or part of the target area, and the target area may include one or more wind field pre-warning areas.

The wind field early warning level can be understood as an early warning level corresponding to each wind field early warning area. In the embodiment of the invention, the wind field early-warning levels corresponding to different wind field early-warning areas can be the same or different.

The rainfall early warning area can be understood as an area needing early warning and having rainfall influence risks. The rainfall early warning area may be all or part of the target area, and the target area may include one or more of the rainfall early warning areas.

The rainfall early warning areas can be understood as early warning levels corresponding to each rainfall early warning area. In the embodiment of the invention, the rainfall early-warning grades corresponding to different rainfall early-warning areas can be the same or different.

It should be understood that the update frequency of the path forecast data is faster, but the forecast content is coarser, and the update frequency of the numerical forecast data is slower, but the forecast content is more detailed, and the technical scheme of the embodiment of the invention effectively fuses the path forecast data and the numerical forecast data to perform typhoon influence forecast, combines the advantages of multidimensional data, and improves the efficiency, the comprehensiveness and the accuracy of typhoon influence forecast.

According to the technical scheme, longitude and latitude coordinates of each path forecasting point in the path forecasting data are determined; and determining the path forecasting point in the target area based on the longitude and latitude coordinates, and determining the first time interval based on the current path forecasting point and the forecasting time corresponding to the current path forecasting point. The effect of accurately determining the time interval of the target typhoon affecting the target area is achieved.

Fig. 6 is an overall flowchart of a typhoon influence prediction method provided according to an embodiment of the present invention, and fig. 7 is an overall algorithm flowchart of a typhoon influence prediction method provided according to an embodiment of the present invention. As shown in fig. 6 and 7, optionally, the overall flow and the overall algorithm flow of the typhoon influence prediction method may be:

1. and acquiring real-time updated path forecast data corresponding to the target typhoon, and calculating a first time interval of the target typhoon affecting the target area through an affecting algorithm.

Algorithmically, after updating path forecast data of a target typhoon, extracting the latest path forecast data, analyzing the path forecast data, and making a data dictionary, wherein a data key is the forecast time corresponding to a path forecast point in the path forecast data, and a value is the longitude and latitude coordinates and/or the central wind speed corresponding to the forecast time; further, the spatial position (longitude and latitude coordinates) of each element (path forecast point) in the data dictionary is analyzed to judge whether the element falls in the spatial range of the target area or not, and then the data dictionary is screened to form a new data dictionary a.

2. A period of time (second time interval) of approximately 3 days (72 hours in the future) is truncated from the first time interval.

Algorithmically, the forecast time of each element of the data dictionary a is determined, and the elements within the range from the current time to 72 hours in the future are screened to form a1. It should be understood that, in order to ensure the rationality of the fusion prediction result, only the data of 3 days in the future are generally fused.

3. And extracting wind field forecast data of the second time interval from the numerical forecast data.

Algorithmically, analyzing the latest numerical forecast data, and extracting wind field forecast data to form a data set B; further, according to the preset time in the a1, wind field forecast data of a corresponding time period is extracted from the data set B to form a data set B, wherein B is a set of data matrixes, and each matrix in the set corresponds to an element of the a1 one by one. Each element in b and each element in a1 are combined to form a dataset b1. b1 is fused data, and after each time data a1 is updated, data can be updated according to the method, and no matter whether data B is updated or not, a new set of B1 is formed.

4. The wind field forecast data is classified according to the four wind power levels of 6, 8, 10 and 12, so that wind field early warning levels, such as blue, yellow, orange and red wind field early warning levels, are obtained. Wherein, blue early warning can represent 6-7 grades of lattice point wind field coverage, yellow early warning can represent 8-9 grades of lattice point wind field coverage, orange early warning can represent 10-11 grades of lattice point wind field coverage, and red early warning can represent 11-12 grades of lattice point wind field coverage.

And (3) algorithmically classifying wind field forecast data at each moment in the b1 data set, wherein the classification is divided according to wind power grades, and four wind field early warning areas of red, orange, yellow and blue are formed by taking a path forecast point as a center, and different wind field early warning areas represent different disaster influence degrees so as to form a data set b2.

5. And extracting rainfall forecast data of the second time interval from the numerical forecast data.

Algorithmically, analyzing the latest numerical forecast data, extracting rainfall variables therein, and forming a dataset C; further, a new set of c1 is formed in the same manner as in step 3 above.

6. And grading the rainfall forecast data according to the four rainfall early warning levels of blue, yellow, orange and red to obtain the rainfall early warning levels, for example, the four rainfall early warning levels of blue, yellow, orange and red. Wherein, blue early warning can be characterized and accumulated that the precipitation reaches 50mm or more in 12 hours, yellow early warning can be characterized and accumulated that the precipitation reaches 50mm or more in 6 hours, orange early warning can be characterized and accumulated that the precipitation reaches 50mm or more in 3 hours, red early warning can be characterized and accumulated that the precipitation reaches 100mm or more in 3 hours.

The rainfall forecast data at each moment in the data set c1 are classified according to the accumulated precipitation amount, four rainfall early warning areas of red, orange, yellow and blue are formed by taking the path forecast point of the target typhoon as the center, different rainfall early warning areas represent different disaster influence degrees, and a data set c2 is formed at the moment.

7. And determining early warning equipment in the transformer substation.

Algorithmically, a data set b2 represents a wind field prediction result of a target typhoon for each path forecast point in a target area in a second time interval, wherein the wind field prediction result comprises a wind field prediction area and a wind field early-warning level corresponding to each wind field early-warning area, and a data set c2 represents a rainfall prediction result of the target typhoon for each path forecast point in the target area in the second time interval, wherein the rainfall prediction result comprises a rainfall prediction area and a rainfall early-warning level corresponding to each rainfall early-warning area; further, spatial correlation judgment is performed according to the spatial positions of power facilities such as a transmission tower, a transformer substation and a power distribution room and the red, orange, yellow and blue positions in the b2 and c2 data, so that four early warning data D of the red, orange, yellow and blue of the power facilities are formed.

The invention can effectively combine typhoon forecast data (namely path forecast data and numerical forecast data) with two different types, different formats, different timeliness, different update frequencies and different forecast contents, solves the problem that the path forecast data and the numerical forecast data are not compatible, improves the accuracy of predicting the influence of target typhoons on electric facilities, and realizes more efficient and finer typhoon influence early warning.

Example III

Fig. 8 is a schematic structural diagram of a typhoon influence prediction device according to a third embodiment of the present invention. As shown in fig. 8, the apparatus includes: a data acquisition module 310, a time determination module 320, and an impact prediction module 330. Wherein,

the data acquisition module 310 is configured to acquire path forecast data corresponding to a target typhoon, and determine a first time interval according to the path forecast data, where the first time interval is a time interval in which the target typhoon affects a target area; a time determining module 320, configured to determine a second time interval based on the first time interval, where the second time interval is an intersection of the predicted time period and the first time interval; the influence prediction module 330 is configured to obtain numerical prediction data corresponding to the target typhoon based on the path prediction data, and determine an influence prediction result of the target typhoon on the target area in the second time interval based on the numerical prediction data.

Wherein, typhoon influence prediction still includes: and the risk early warning module is used for determining early warning equipment in the target area based on the influence prediction result and carrying out risk early warning on the early warning equipment.

Optionally, the path forecast data includes a plurality of path forecast points, and longitude and latitude coordinates and forecast time corresponding to each of the path forecast points, the target area includes at least one path forecast point, and the data acquisition module 310 is configured to:

determining longitude and latitude coordinates of each path forecasting point in the path forecasting data;

and determining the path forecasting point in the target area based on the longitude and latitude coordinates, and determining the first time interval based on the current path forecasting point and the forecasting time corresponding to the current path forecasting point.

Optionally, the impact prediction module 330 includes: a numerical data obtaining unit, configured to determine the forecast time of each path forecast point in the target area, and obtain the numerical forecast data corresponding to each path forecast point based on the forecast time.

Optionally, the impact prediction module 330 includes: and the influence prediction unit is used for determining an influence prediction result of the target typhoon on each path prediction point in the target area in the second time interval based on the numerical prediction data, wherein the influence prediction result comprises at least one target early-warning area corresponding to each path prediction point and a target early-warning level corresponding to each target early-warning area.

Optionally, the numerical forecast data includes wind field forecast data and/or rainfall forecast data, and the influence prediction unit includes: a sub-result determination sub-unit and an influence result determination sub-unit; wherein,

the sub-result determining sub-unit is used for respectively determining a wind field influence result and a rainfall influence result of the target typhoon on each path forecast point in the target area in the second time interval based on the wind field forecast data and the rainfall forecast data;

the influence result determination subunit is configured to determine the influence prediction result based on the wind field influence result and the rainfall influence result.

the influence result determination subunit is configured to:

The typhoon influence prediction device provided by the embodiment of the invention can execute the typhoon influence prediction method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

Example IV

Fig. 9 shows a schematic diagram of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.

As shown in fig. 9, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.

Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the respective methods and processes described above, such as the typhoon influence prediction method.

In some embodiments, the typhoon impact prediction method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the typhoon impact prediction method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the typhoon impact prediction method by any other suitable means (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.

The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.

The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.

Claims

1. A typhoon impact prediction method, comprising:

And acquiring numerical forecasting data corresponding to the target typhoon based on the path forecasting data, and determining an influence forecasting result of the target typhoon on the target area in the second time interval based on the numerical forecasting data.

2. The method as recited in claim 1, further comprising:

3. The method of claim 1, wherein the path forecast data includes a plurality of path forecast points and latitude and longitude coordinates and a forecast time corresponding to each of the path forecast points, the target area includes at least one of the path forecast points, and the determining a first time interval from the path forecast data includes:

4. A method according to claim 3, wherein said obtaining numerical forecast data corresponding to the target typhoon based on the path forecast data comprises:

5. The method of claim 4, wherein the determining, based on the numerical forecast data, a predicted outcome of an effect of the target typhoon on the target area within the second time interval comprises:

6. The method according to claim 5, wherein the numerical forecast data comprises wind farm forecast data and/or rainfall forecast data, and wherein the determining, based on the numerical forecast data, a predicted outcome of the influence of the target typhoon on each of the path forecast points in the target area over the second time interval comprises:

7. The method of claim 6, wherein the wind farm impact results comprise at least one wind farm pre-warning area and a wind farm pre-warning level corresponding to each of the wind farm pre-warning areas, the rainfall impact results comprise at least one rainfall pre-warning area and a rainfall pre-warning level corresponding to each of the rainfall pre-warning areas,

8. A typhoon influence prediction apparatus, comprising:

9. An electronic device, the electronic device comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the typhoon impact prediction method of any one of claims 1-7.

10. A computer readable storage medium storing computer instructions for causing a processor to implement the typhoon impact prediction method of any one of claims 1-7 when executed.