Typhoon disaster loss estimation method and device, computer equipment and storage medium

Abstract

The invention provides a typhoon disaster loss estimation method and device, computer equipment and a storage medium. The method comprises the following steps: determining predicted path information of a typhoon to be estimated before a landing time point; determining similar typhoons from the plurality of historical typhoons according to the predicted path information; obtaining a reference claim amount corresponding to each similar typhoon; and according to the reference claim settlement amount, determining an estimated claim settlement amount of the to-be-estimated typhoon. By implementing the method disclosed by the invention, the estimated claim amount of the to-be-estimated typhoon can be quickly and accurately obtained based on the similar typhoons, and the reliability of the obtained estimated claim amount is effectively improved.

Description

Technical Field

[0001] The present disclosure relates to the field of software development technology, and in particular to a typhoon disaster loss estimation method, device, computer equipment and storage medium. Background Art

[0002] In the insurance field, it is usually necessary to estimate the losses of a typhoon that is about to make landfall in order to provide a reference for insurance companies' decision-making.

[0003] In the prior art, when estimating typhoon disaster losses, the focus is on algorithm research on similar typhoons themselves, including research on the similarities of typhoon paths, intensities, characteristics, etc., so as to forecast and assess the impact of newly formed typhoons.

[0004] In this way, the calculation cost is high and the reliability of the loss estimation results cannot be guaranteed. Summary of the invention

[0005] The present disclosure aims to solve one of the technical problems in the related art at least to some extent.

[0006] To this end, the purpose of the present disclosure is to propose a typhoon disaster loss estimation method, device, computer equipment and storage medium, thereby being able to quickly and accurately obtain the estimated claim amount of the typhoon to be estimated based on similar typhoons, and effectively improve the reliability of the estimated claim amount obtained.

[0007] To achieve the above-mentioned purpose, the typhoon disaster loss estimation method proposed in the first embodiment of the present disclosure includes:

[0008] Determine the predicted path information of the typhoon to be estimated before the landing time point;

[0009] Determining similar typhoons from multiple historical typhoons according to the predicted path information;

[0010] Obtain the reference claim amount corresponding to each of the similar typhoons;

[0011] Based on the reference claim amount, the estimated claim amount of the to-be-estimated typhoon is determined.

[0012] To achieve the above-mentioned purpose, a typhoon disaster loss prediction device proposed in a second embodiment of the present disclosure includes:

[0013] The first determination module is used to determine the predicted path information of the typhoon to be estimated before the landing time point;

[0014] A second determination module is used to determine similar typhoons from multiple historical typhoons according to the predicted path information;

[0015] An acquisition module, used for acquiring a reference claim amount corresponding to each of the similar typhoons;

[0016] The third determination module is used to determine the estimated claim amount of the typhoon to be estimated based on the reference claim amount.

[0017] The computer device proposed in the third aspect embodiment of the present disclosure includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the typhoon disaster loss prediction method proposed in the first aspect embodiment of the present disclosure is implemented.

[0018] The fourth aspect embodiment of the present disclosure proposes a non-temporary computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the typhoon disaster loss estimation method proposed in the first aspect embodiment of the present disclosure is implemented.

[0019] The fifth aspect embodiment of the present disclosure proposes a computer program product. When the instructions in the computer program product are executed by a processor, the typhoon disaster loss prediction method proposed in the first aspect embodiment of the present disclosure is executed.

[0020] The typhoon disaster loss estimation method, device, computer equipment and storage medium provided by the present disclosure determine the predicted path information of the typhoon to be estimated before the landing time point; determine similar typhoons from multiple historical typhoons based on the predicted path information; obtain the reference claim amount corresponding to each similar typhoon; and determine the estimated claim amount of the typhoon to be estimated based on the reference claim amount. As a result, the estimated claim amount of the typhoon to be estimated can be obtained quickly and accurately based on similar typhoons, and the reliability of the obtained estimated claim amount can be effectively improved.

[0021] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description or learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and / or additional aspects and advantages of the present disclosure will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0023] Figure 1 is a flow chart of a typhoon disaster loss estimation method proposed in an embodiment of the present disclosure;

[0024] Figure 2 is a flow chart of a typhoon disaster loss estimation method proposed in another embodiment of the present disclosure;

[0025] Figure 3 is a schematic diagram of similarity calculation proposed in the present disclosure;

[0026] Figure 4 is a structural schematic diagram of a typhoon disaster loss estimation device proposed in an embodiment of the present disclosure;

[0027] Figure 5 A block diagram of an exemplary computer device suitable for implementing embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0028] Embodiments of the present disclosure are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present disclosure, and are not to be construed as limitations of the present disclosure. On the contrary, the embodiments of the present disclosure include all changes, modifications, and equivalents that fall within the spirit and connotation of the appended claims.

[0029] Figure 1 It is a flowchart of a typhoon disaster loss estimation method proposed in an embodiment of the present disclosure.

[0030] It should be noted that the executor of the typhoon disaster loss estimation method of this embodiment is a typhoon disaster loss estimation device, which can be implemented by software and / or hardware. The device can be configured in a computer device, and the computer device can include but is not limited to a terminal, a server, etc. For example, the terminal can be a mobile phone, a handheld computer, etc.

[0031] like Figure 1 As shown in FIG. 1 , the typhoon disaster loss estimation method includes:

[0032] S101: Determine the predicted path information of the typhoon to be estimated before the landing time point.

[0033] The typhoon to be estimated refers to a typhoon for which disaster loss estimation is to be performed in the embodiment of the present disclosure. The typhoon to be estimated may be a typhoon predicted by the Meteorological Bureau to land on land.

[0034] Among them, the landing time point refers to the predicted time point when the typhoon is about to land on land.

[0035] The predicted path information may be used to indicate the movement path of the typhoon to be estimated before the landing time point, and may include, for example, the predicted path trajectory.

[0036] In the disclosed embodiment, when determining the predicted path information of the to-be-estimated typhoon before the landing time point, the relevant information may be obtained from the meteorological warning system of the area where the to-be-estimated typhoon is located.

[0037] In the disclosed embodiment, when the predicted path information of the typhoon to be estimated before the landing time point is determined, reliable data support can be provided for the subsequent determination of similar typhoons.

[0038] S102: Determine similar typhoons from multiple historical typhoons based on the predicted path information.

[0039] Among them, historical typhoons refer to typhoons that have made landfall in the area where the typhoon is to be predicted.

[0040] Among them, similar typhoons refer to typhoons that have a high similarity with the above-mentioned typhoons to be predicted.

[0041] In the disclosed embodiment, when determining similar typhoons from multiple historical typhoons based on predicted path information, the path information corresponding to the multiple historical typhoons may be obtained, and then a method combining numbers and shapes may be used to determine similar typhoons from the multiple historical typhoons based on the predicted path information and the path information corresponding to the multiple historical typhoons. Alternatively, the predicted path information and the path information corresponding to the multiple historical typhoons may be input into a pre-trained machine learning model to determine similar typhoons from multiple historical typhoons, and there is no limitation to this.

[0042] Optionally, in some embodiments, the predicted path information includes: multiple predicted path points; wherein, when determining similar typhoons from multiple historical typhoons based on the predicted path information, it can be: determining a buffer area corresponding to each predicted path point based on a preset radius; obtaining a historical typhoon path corresponding to each historical typhoon; determining an intersection operation result between the buffer area and the historical typhoon path; and determining similar typhoons from multiple historical typhoons based on the intersection operation result. Thus, similar typhoons can be quickly and accurately determined from multiple historical typhoons based on the intersection algorithm.

[0043] Among them, the predicted path point refers to the location point where the typhoon is expected to pass.

[0044] In the disclosed embodiment, multiple predicted paths of the typhoon to be estimated may be obtained, and then the predicted path points may be selected from the overlapping points of the multiple predicted paths.

[0045] The preset radius may refer to a radius pre-set for the predicted path point for determining the buffer area.

[0046] The buffer area may refer to a circular area with the predicted path point as the center and a preset radius as the radius.

[0047] Among them, the historical typhoon path may refer to the moving path corresponding to the historical typhoon.

[0048] Among them, the intersection operation result can be used to indicate the intersection of the buffer area and the historical typhoon path.

[0049] In the embodiment of the present disclosure, when similar typhoons are determined from multiple historical typhoons based on the intersection operation results, typhoons whose historical typhoon paths pass through all buffer areas can be regarded as similar typhoons. That is, in the embodiment of the present disclosure, after determining the predicted path information of the typhoon to be estimated before the landing time point, similar typhoons can be determined from multiple historical typhoons based on the predicted path information, thereby providing reliable reference information for subsequent loss estimation.

[0050] S103: Obtain the reference claim amount corresponding to each similar typhoon.

[0051] Among them, the reference claim amount refers to the claim amount corresponding to similar typhoons as a reference. The reference claim amount can be determined in combination with the actual claim amount of similar typhoons.

[0052] In the disclosed embodiment, when the reference claim amount corresponding to each similar typhoon is obtained, reliable reference information can be provided for the subsequent determination of the estimated claim amount of the typhoon to be estimated.

[0053] S104: Determine the estimated claim amount for the typhoon to be estimated based on the reference claim amount.

[0054] Among them, the estimated claim amount refers to the claim amount for the estimated typhoon determined based on the reference claim amount.

[0055] In the embodiments of the present disclosure, when determining the estimated claim amount of the typhoon to be estimated based on the reference claim amount, multiple reference claim amounts can be input into a pre-trained machine learning model to obtain the estimated claim amount, or the estimated claim amount of the typhoon to be estimated can be determined based on the reference claim amount based on engineering or mathematical methods, and there is no limitation to this.

[0056] In this embodiment, by determining the predicted path information of the typhoon to be estimated before the landing time point; determining similar typhoons from multiple historical typhoons based on the predicted path information; obtaining the reference claim amount corresponding to each similar typhoon; and determining the estimated claim amount of the typhoon to be estimated based on the reference claim amount. In this way, the estimated claim amount of the typhoon to be estimated can be obtained quickly and accurately based on similar typhoons, and the reliability of the obtained estimated claim amount can be effectively improved.

[0057] Figure 2 It is a flowchart of a typhoon disaster loss estimation method proposed in another embodiment of the present disclosure.

[0058] like Figure 2 As shown in FIG. 1 , the typhoon disaster loss estimation method includes:

[0059] S201: Determine the predicted path information of the typhoon to be estimated before the landing time point, wherein the predicted path information includes: a plurality of predicted path points.

[0060] S202: Determine a buffer area corresponding to each predicted path point based on a preset radius.

[0061] S203: Obtain the historical typhoon path corresponding to each historical typhoon.

[0062] S204: Determine the intersection operation result of the buffer area and the historical typhoon path.

[0063] The description of S201 - S204 can be specifically referred to the above embodiment, which will not be repeated here.

[0064] S205: If the intersection operation result indicates that the historical typhoon path intersects with the buffer area, the corresponding historical typhoon is used as a candidate typhoon.

[0065] The candidate typhoon may refer to a typhoon that intersects with the buffer area based on the intersection calculation result.

[0066] That is, in the embodiments of the present disclosure, a preliminary screening of multiple historical typhoons can be implemented based on the intersection operation results to determine candidate typhoons.

[0067] S206: Determine the target similarity between the typhoon to be estimated and the candidate typhoons based on the multiple predicted path points.

[0068] Among them, the target similarity can be used to indicate the similarity between the typhoon to be estimated and the candidate typhoon.

[0069] In the embodiments of the present disclosure, when determining the target similarity between the typhoon to be estimated and the candidate typhoon based on multiple predicted path points, the target similarity can be determined based on a method combining numbers and shapes according to multiple predicted path points and historical typhoon paths, or, the multiple predicted path points and historical typhoon paths can be input into a pre-trained machine learning model to obtain the corresponding target similarity.

[0070] Optionally, in some embodiments, when determining the target similarity between the typhoon to be estimated and the candidate typhoon based on multiple predicted path points, the path position similarity can be determined based on multiple predicted path points and historical typhoon paths; the path shape similarity can be determined based on multiple predicted path points, historical typhoon paths, and path position similarity; and the average of the path position similarity and the path shape similarity can be determined as the target similarity. Thus, the indication accuracy of the obtained target similarity can be effectively improved by combining the path position similarity and the path shape similarity.

[0071] Among them, the path position similarity can be used to indicate the similarity between the typhoon to be estimated and the candidate typhoon in the path position dimension, and the path shape similarity can be used to indicate the similarity between the typhoon to be estimated and the candidate typhoon in the path shape dimension.

[0072] S207: Determine similar typhoons from multiple candidate typhoons according to the target similarity.

[0073] In the embodiment of the present disclosure, when determining similar typhoons from a plurality of candidate typhoons based on target similarity, one or more candidate typhoons with the highest target similarity may be selected as similar typhoons.

[0074] That is, in the embodiment of the present disclosure, after determining the intersection operation result of the buffer area and the historical typhoon path, if the intersection operation result indicates that the historical typhoon path intersects with the buffer area, the corresponding historical typhoon is used as a candidate typhoon; based on multiple predicted path points, the target similarity between the typhoon to be estimated and the candidate typhoon is determined; based on the target similarity, a similar typhoon is determined from multiple candidate typhoons. In this way, the reliability of the similar typhoon determination process can be effectively improved, and the practicality of the obtained similar typhoon can be guaranteed.

[0075] S208: Determine the historical claim amounts for similar typhoons and the historical resident price index for the corresponding years.

[0076] Among them, the historical claim amount may refer to the insurance claim amount caused by similar typhoons mentioned above.

[0077] Among them, the historical residential price index refers to the residential price index corresponding to the years when similar typhoons occurred.

[0078] In the disclosed embodiment, when determining the historical claim amounts of similar typhoons and the historical resident price index of the corresponding year, reliable reference information can be provided for the subsequent determination of the correction coefficient and the reference claim amount.

[0079] S209: Determine the current resident price index for the year corresponding to the typhoon to be estimated.

[0080] The current resident price index may refer to the resident price index of the year corresponding to the to-be-forecasted typhoon. If the resident price index of the year of the to-be-forecasted typhoon is not available, the resident price index of the previous year may be obtained as the current resident price index.

[0081] In the disclosed embodiment, when determining the current resident price index for the year corresponding to the typhoon to be predicted, reliable data support can be provided for the subsequent determination of the correction coefficient.

[0082] S210: Determine a correction coefficient based on the historical resident price index and the current resident price index.

[0083] Among them, the correction coefficient refers to the coefficient used to correct the historical claim amount.

[0084] In the embodiment of the present disclosure, when determining the correction coefficient based on the historical resident price index and the current resident price index, the historical resident price index and the current resident price index can be substituted into a preset formula to calculate the correction coefficient, or the correction coefficient can be determined based on the historical resident price index and the current resident price index based on a method combining numbers and shapes, and there is no limitation on this.

[0085] S211: Determine the product of the historical claim amount and the correction coefficient as the reference claim amount.

[0086] That is, in the disclosed embodiment, the historical claim amount of similar typhoons and the historical resident price index of the corresponding year can be determined; the current resident price index of the corresponding year of the estimated typhoon can be determined; the correction coefficient can be determined based on the historical resident price index and the current resident price index; the product value of the historical claim amount and the correction coefficient can be determined as the reference claim amount. Thus, the applicable correction coefficient can be accurately and quickly calculated based on the historical resident price index and the current resident price index, and the adaptive adjustment of the historical claim amount can be achieved based on the correction coefficient, so as to ensure the applicability of the obtained reference claim amount.

[0087] S212: Determine a weight value corresponding to each reference claim amount based on the target similarity.

[0088] The weight value may be used to indicate the weight of the reference claim amount in calculating the estimated claim amount. The weight value may be positively correlated with the target similarity.

[0089] In the embodiments of the present disclosure, when determining the weight value corresponding to each reference claim amount based on the target similarity, all target similarities can be input into a pre-trained machine learning model to obtain the corresponding weight value, or the weight value corresponding to each reference claim amount can be determined based on the target similarity based on a method combining numbers and shapes, and there is no limitation on this.

[0090] S213: Perform weighted summation on the reference claim amounts based on the weight values ​​to obtain an estimated claim amount.

[0091] That is, in the embodiment of the present disclosure, the weight value corresponding to each reference claim amount can be determined according to the target similarity; the reference claim amounts are weighted and summed based on the weight value to obtain the estimated claim amount. Thus, the reliability and practicality of the obtained estimated claim amount can be guaranteed.

[0092] In this embodiment, after determining the intersection operation result of the buffer area and the historical typhoon path, if the intersection operation result indicates that the historical typhoon path intersects with the buffer area, the corresponding historical typhoon is used as a candidate typhoon; based on multiple predicted path points, the target similarity between the typhoon to be estimated and the candidate typhoon is determined; based on the target similarity, a similar typhoon is determined from multiple candidate typhoons. In this way, the reliability of the similar typhoon determination process can be effectively improved, and the practicality of the obtained similar typhoons can be guaranteed. By determining the historical claim amount of similar typhoons and the historical resident price index of the corresponding year; determining the current resident price index of the corresponding year of the typhoon to be estimated; determining the correction coefficient based on the historical resident price index and the current resident price index; determining the product value of the historical claim amount and the correction coefficient as the reference claim amount. In this way, the applicable correction coefficient can be accurately and quickly calculated based on the historical resident price index and the current resident price index, and the adaptive adjustment of the historical claim amount can be achieved based on the correction coefficient to ensure the applicability of the obtained reference claim amount. By determining the weight value corresponding to each reference claim amount according to the target similarity, and performing weighted summation of the reference claim amounts based on the weight value, an estimated claim amount is obtained, thereby ensuring the reliability and practicality of the obtained estimated claim amount.

[0093] Based on the above embodiments, the present disclosure may be based on the following steps when estimating typhoon disaster losses:

[0094] 1) Extract typhoon path dataset

[0095] Extract the tropical cyclone path dataset for multiple years in the specified area. This dataset contains information such as the path, intensity, wind speed, and air pressure of tropical cyclones (the recording interval is generally no longer than 6 hours).

[0096] 2) Preliminary screening by buffer overlay analysis (screening position and shape)

[0097] When the typhoon path point predicted by the Meteorological Bureau lands on land, determine the path points within 16 hours before the landing time. Take the path points within 16 hours as the center and a radius of 200km for buffer analysis, and then perform an intersection operation with the historical typhoon path linear elements. Solve the intersection of the two to obtain the typhoon path within the buffer zone. Then use the corresponding typhoon as a similar typhoon that meets the conditions in this step.

[0098] 3) Calculate the similarity of the typhoon paths passing through the buffer zone

[0099] The similarity deviation method regards the typhoon path as a set of curves in a two-dimensional plane. It mainly measures the similarity of the typhoon paths by judging the similarity of the positions and shapes of the typhoon paths and then taking the average of the two. Figure 3 As shown, Figure 3It is a schematic diagram of similarity deviation calculation proposed in the present disclosure.

[0100]

[0101] D ij ----The average value of the longitudinal height difference of the typhoon path control points (km);

[0102] M----The number of typhoon path control points selected;

[0103] Y ik ----The longitudinal coordinate value of the kth path control point on the i-th typhoon path (km);

[0104] Y jk ----The longitudinal coordinate value of the kth path control point on the jth typhoon path (km);

[0105] In the figure, the solid line is i, and the dotted line is j. The longitude and latitude coordinates are converted into XY coordinates through coordinate transformation. The points of the typhoon path separated by a certain distance are used as control points. The longitudinal position difference between the two typhoon paths is expressed by the above formula.

[0106] The shape of the typhoon path is calculated using the following formula. The smaller the value, the closer the shapes of the two typhoon paths are.

[0107]

[0108] Si j ----Typhoon path shape coefficient, other meanings are consistent with the above formula.

[0109] 4) Calculate the estimated loss amount for each province

[0110] The similarity is sorted from low to high, and the three typhoons with the lowest similarity are selected. The actual claims of these three most similar typhoons are calculated by province, and then weighted and graded (coefficient conversion is performed based on distance, intensity, etc.) using CPI (after adjusting for inflation coefficient). The final claim amount is used as the estimated loss amount for each province in this typhoon.

[0111] Claim amount correction: Direct economic losses are normalized using CPI, which is the resident price index:

[0112]

[0113] DEL N =λ*DELP P

[0114] CPI N : CPI index one year before the target typhoon;

[0115] N: the difference between the target typhoon and similar historical typhoons (years);

[0116] CPIp: CPI index of similar typhoons in history;

[0117] DEL N : The revised claim amount;

[0118] DELp: claim amount before correction;

[0119] Typhoon similarity weight calculation (for multiple typhoons):

[0120]

[0121] n: the number of similar typhoons involved in the forecast;

[0122] S i : The similarity between the i-th similar typhoon and the current target typhoon;

[0123] W i : The proportion of the i-th similar typhoon;

[0124] Weighted calculation of estimated losses:

[0125]

[0126] DEL: Weighted claim amount.

[0127] Figure 4 It is a structural schematic diagram of a typhoon disaster loss estimation device proposed in one embodiment of the present disclosure.

[0128] like Figure 4 As shown, the typhoon disaster loss estimation device 40 includes:

[0129] The first determination module 401 is used to determine the predicted path information of the typhoon to be estimated before the landing time point;

[0130] A second determination module 402 is used to determine similar typhoons from multiple historical typhoons according to the predicted path information;

[0131] An acquisition module 403 is used to acquire a reference claim amount corresponding to each similar typhoon;

[0132] The third determination module 404 is used to determine the estimated claim amount of the to-be-estimated typhoon according to the reference claim amount.

[0133] It should be noted that the aforementioned explanation of the typhoon disaster loss estimation method is also applicable to the typhoon disaster loss estimation device of this embodiment, and will not be repeated here.

[0134] In this embodiment, by determining the predicted path information of the typhoon to be estimated before the landing time point; determining similar typhoons from multiple historical typhoons based on the predicted path information; obtaining the reference claim amount corresponding to each similar typhoon; and determining the estimated claim amount of the typhoon to be estimated based on the reference claim amount. In this way, the estimated claim amount of the typhoon to be estimated can be obtained quickly and accurately based on similar typhoons, and the reliability of the obtained estimated claim amount can be effectively improved.

[0135] Figure 5 A block diagram of an exemplary computer device suitable for implementing embodiments of the present disclosure is shown. Figure 5 The computer device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0136] like Figure 5 As shown, the computer device 12 is in the form of a general-purpose computing device. The components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0137] The bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor or a local bus using any of a variety of bus structures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Peripheral Component Interconnection (PCI) bus.

[0138] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0139] The memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 5 Not shown, often called a "hard drive").

[0140] although Figure 5 Not shown, a disk drive for reading and writing a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing a removable non-volatile optical disk (e.g., a compact disc read only memory (Compact Disc Read Only Memory; hereinafter referred to as: CD-ROM), a digital versatile disc read only memory (Digital Video Disc Read Only Memory; hereinafter referred to as: DVD-ROM) or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present disclosure.

[0141] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in the memory 28, such program modules 42 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 42 generally perform the functions and / or methods of the embodiments described in the present disclosure.

[0142] The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a human body to interact with the computer device 12, and / or any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed via an input / output (I / O) interface 22. In addition, the computer device 12 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with other modules of the computer device 12 via a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the computer device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0143] The processing unit 16 executes various functional applications and data processing by running the programs stored in the system memory 28, such as implementing the typhoon disaster loss estimation method mentioned in the above embodiment.

[0144] In order to implement the above embodiments, the present disclosure further proposes a non-temporary computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the typhoon disaster loss prediction method proposed in the above embodiments of the present disclosure is implemented.

[0145] In order to implement the above embodiments, the present disclosure further proposes a computer program product. When the instruction processor in the computer program product is executed, the typhoon disaster loss prediction method proposed in the above embodiments of the present disclosure is executed.

[0146] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0147] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

[0148] It should be noted that, in the description of the present disclosure, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present disclosure, unless otherwise specified, the meaning of "plurality" is two or more.

[0149] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present disclosure includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present disclosure belong.

[0150] It should be understood that the various parts of the present disclosure can be implemented in hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0151] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0152] In addition, each functional unit in each embodiment of the present disclosure may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0153] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0154] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0155] Although the embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present disclosure. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present disclosure.

Claims

1. A method for estimating typhoon disaster losses, characterized in that: include: Determine the predicted path information of the typhoon to be estimated before the landing time point; Determining similar typhoons from multiple historical typhoons according to the predicted path information; Obtain the reference claim amount corresponding to each of the similar typhoons; Based on the reference claim amount, the estimated claim amount of the to-be-estimated typhoon is determined.

2. The method according to claim 1, characterized in that The predicted path information includes: a plurality of predicted path points; Wherein, determining similar typhoons from multiple historical typhoons according to the predicted path information includes: Determining a buffer area corresponding to each of the predicted path points based on a preset radius; Obtain the historical typhoon path corresponding to each of the historical typhoons; Determining the intersection operation result of the buffer area and the historical typhoon path; According to the intersection operation result, the similar typhoon is determined from the multiple historical typhoons.

3. The method according to claim 2, characterized in that Determining the similar typhoon from the plurality of historical typhoons according to the intersection operation result includes: If the intersection operation result indicates that the historical typhoon path intersects with the buffer area, the corresponding historical typhoon is used as a candidate typhoon; Based on the multiple predicted path points, determining the target similarity between the typhoon to be estimated and the candidate typhoon; The similar typhoon is determined from the plurality of candidate typhoons according to the target similarity.

4. The method according to claim 3, characterized in that The determining, based on the multiple predicted path points, the target similarity between the typhoon to be estimated and the candidate typhoons comprises: Determining path position similarity based on the multiple predicted path points and the historical typhoon path; Determining path shape similarity based on the multiple predicted path points, the historical typhoon paths, and the path position similarity; An average value of the path position similarity and the path shape similarity is determined as the target similarity.

5. The method according to claim 1, characterized in that The obtaining of the reference claim amount corresponding to each similar typhoon includes: Determine the historical claims amount for similar typhoons and the historical residential price index for the corresponding years; Determine the current resident price index for the year corresponding to the typhoon to be estimated; Determining a correction factor based on the historical resident price index and the current resident price index; The product of the historical claim amount and the correction coefficient is determined as the reference claim amount.

6. The method according to claim 3, characterized in that Determining the estimated claim amount of the to-be-estimated typhoon based on the reference claim amount includes: Determining a weight value corresponding to each of the reference claim amounts according to the target similarity; The reference claim amounts are weighted and summed based on the weight values ​​to obtain the estimated claim amount.

7. A typhoon disaster loss estimation device, characterized in that: include: The first determination module is used to determine the predicted path information of the typhoon to be estimated before the landing time point; A second determination module is used to determine similar typhoons from multiple historical typhoons according to the predicted path information; An acquisition module, used for acquiring a reference claim amount corresponding to each of the similar typhoons; The third determination module is used to determine the estimated claim amount of the typhoon to be estimated based on the reference claim amount.

8. A computer device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: in, The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 6.

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