A method, device and equipment for predicting a typhoon storm surge danger level parameter

Abstract

This invention provides a method, apparatus, and equipment for predicting storm surge hazard level parameters for typhoons, relating to the field of storm surge data processing. The method includes: acquiring target characteristic parameters of the current typhoon in the target area and a preset storm surge intensity level index comparison table for the target area; inputting the target characteristic parameters into a preset storm surge prediction model, and outputting prediction results through the preset storm surge prediction model; wherein the preset storm surge prediction model is determined using multiple sets of historical typhoon data for the current target area; and determining the hazard level parameters of the current storm surge in the current target area based on the prediction results and the preset storm surge intensity level index comparison table for the target area. The solution of this invention achieves real-time prediction of storm surge hazard level parameters for the current area under extreme environments, and has the advantages of fast prediction speed and easy interpretation of prediction results.

Description

Technical Field

[0001] This invention relates to the field of storm surge data processing, and in particular to a method, apparatus, and equipment for predicting typhoon storm surge hazard level parameters. Background Technology

[0002] Storm surge refers to the abnormal rise in sea level caused by strong atmospheric disturbances. Depending on the weather system that triggers it, storm surges are classified as typhoon storm surges and extratropical storm surges. Typhoon storm surge disasters are among the most significant marine disasters. Coastal cities are frequently hit by typhoon storm surges, and areas with funnel-shaped topography are also highly susceptible to storm surge disasters. Currently, operational storm surge forecasts largely rely on numerical calculations. However, numerical models depend on ultra-high-performance computers, consuming substantial computing resources. Furthermore, the operation and interpretation of these models require a certain level of mathematical and physical understanding, making them difficult for non-professionals to use. Existing forecasting methods primarily provide large-scale, uniform predictions, failing to provide real-time, rapid forecasts tailored to specific locations. This leaves remote areas or special environments where non-professionals, lacking high-performance computers, unable to independently predict storm surges based on local conditions, hindering preventative disaster prevention measures and subsequent rescue efforts. Summary of the Invention

[0003] The technical problem this invention aims to solve is how to provide a method, apparatus, and equipment for predicting typhoon storm surge hazard level parameters. It addresses the shortcomings of existing storm surge prediction methods, such as the inability to predict storm surges in real-time under extreme conditions based on local environmental information, the difficulty in interpreting prediction results, and high costs.

[0004] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: Embodiments of the present invention provide a method for predicting typhoon storm surge hazard level parameters, including: Obtain the target characteristic parameters of the current typhoon in the target area and the reference table of the preset storm surge intensity level index of the target area; The target feature parameters are input into a preset storm surge prediction model, and the prediction results are output through the preset storm surge prediction model; wherein, the preset storm surge prediction model is determined by multiple sets of historical typhoon data for the current target area; Based on the prediction results and the preset storm surge intensity level index comparison table for the target area, the current storm surge hazard level parameter for the current target area is determined.

[0005] Optionally, obtain a preset storm surge intensity level index reference table for the target area, including: Obtain multiple sets of maximum water surge parameters during historical typhoon storm surges from the two tide level observation stations closest to the target area; Based on the maximum water increase parameters during multiple sets of historical typhoon storm surges, the interval parameters for storm surge intensity levels were determined. Based on the interval parameters and the number of preset levels, a preset storm surge intensity level index comparison table for the target area is determined.

[0006] Optionally, based on multiple sets of historical typhoon data for the current target area, the preset storm surge prediction model is determined, including: Obtain multiple sets of preset initial impact factors; wherein each set of preset initial impact factors includes at least five different initial impact factors; Based on the preset storm surge intensity index comparison table for the target area, determine the storm surge intensity level corresponding to each set of historical typhoon data; Based on each set of historical typhoon data for the current target area and the storm surge intensity level corresponding to each set of historical typhoon data, determine the parameter values ​​of each initial impact factor in each set of preset initial impact factors and the storm surge intensity level corresponding to each set of preset initial impact factors. Based on the parameter values ​​of each initial impact factor in each set of preset initial impact factors and the storm surge intensity level corresponding to each set of preset initial impact factors, determine the correlation parameter value between each initial impact factor and the storm surge intensity level; The target impact factor of the prediction model is determined based on the correlation parameter values ​​between each initial impact factor and the storm surge intensity level. Based on the target parameter factors, a preset storm surge prediction model is determined.

[0007] Optionally, based on a preset storm surge intensity index reference table for the target area, determine the storm surge intensity level corresponding to each set of historical typhoon data, including: Obtain the first and second maximum water level increases corresponding to the two tide level observation stations closest to the target area during each historical typhoon period; Based on the first maximum water increase, the second maximum water increase, and the preset storm surge intensity index of the target area corresponding to each set of historical typhoon data, the storm surge intensity level corresponding to each set of historical typhoon data is determined.

[0008] Optionally, based on the parameter values ​​of each initial impact factor in each set of preset initial impact factors and the storm surge intensity level corresponding to each set of preset initial impact factors, determine the correlation parameter value between each initial impact factor and the storm surge intensity level, including: Through formula Determine the correlation parameter values ​​between each initial influencing factor and the storm surge intensity level; in, This represents the correlation parameter value between the j-th initial influencing factor and the storm surge intensity level; n represents the number of preset initial influencing factors. This represents the parameter value of the j-th initial impact factor in the i-th group of preset initial impact factors; This represents the storm surge intensity level value corresponding to the j-th initial impact factor in the i-th group of preset initial impact factors; This represents the average value of all j-th initial influence factor parameters; This represents the average storm surge intensity level value of all j-th initial influencing factors.

[0009] Optionally, based on the correlation parameter values ​​between each initial impact factor and the storm surge intensity level, the target impact factors of the prediction model are determined, including: Based on the correlation parameter values ​​between each initial impact factor and the storm surge intensity level, the initial impact factors are subjected to a first screening process using a first preset value and a first preset rule to obtain the first impact factor. Based on the preset number of target impact factors and the correlation value of the first impact factor, the first impact factor is subjected to a second screening process to obtain the target parameter factors of the prediction model.

[0010] Optionally, a preset storm surge prediction model is determined based on the target parameter factors, including: Based on the correlation parameter values ​​of the target parameter factors, the obtained preset number of target influence factors are sorted from largest to smallest, and then processed using the formula... Determine the preset storm surge prediction model; Where x1 is the first target impact factor after ranking; x2 is the second target impact factor after ranking; x3 is the third target impact factor after ranking; x4 is the fourth target impact factor after ranking; and x5 is the fifth target impact factor after ranking.

[0011] Embodiments of the present invention also provide a device for predicting typhoon storm surge hazard level parameters, comprising: The acquisition module is used to acquire the target characteristic parameters of the current typhoon in the target area and the preset storm surge intensity level index comparison table of the target area; The processing module is used to input the target feature parameters into a preset storm surge prediction model and output the prediction results through the preset storm surge prediction model; wherein, the preset storm surge prediction model is determined by multiple sets of historical typhoon data of the current target area; and the current storm surge hazard level parameters of the current target area are determined according to the prediction results and the preset storm surge intensity level index comparison table of the target area.

[0012] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when run by the processor, executes the above-described method for predicting typhoon storm surge hazard level parameters.

[0013] Embodiments of the present invention also provide a computer-readable storage medium, comprising: stored instructions, which, when executed on a computer, cause the computer to perform the above-described method for predicting typhoon storm surge hazard level parameters.

[0014] The above-described solution of the present invention has at least the following beneficial effects: The method for predicting typhoon storm surge hazard level parameters according to the present invention includes: acquiring target characteristic parameters of the current typhoon in the target area and a preset storm surge intensity level index comparison table for the target area; inputting the target characteristic parameters into a preset storm surge prediction model, and outputting prediction results through the preset storm surge prediction model; wherein, the preset storm surge prediction model is determined by multiple sets of historical typhoon data for the current target area; and determining the hazard level parameters of the current storm surge in the current target area based on the prediction results and the preset storm surge intensity level index comparison table for the target area. This method achieves real-time prediction of storm surge hazard level parameters in the current area under extreme environments, and has the advantages of fast prediction speed and easy interpretation of prediction results. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating the method for predicting typhoon storm surge hazard level parameters according to an embodiment of the present invention. Figure 2 This is a schematic diagram of a module for predicting typhoon storm surge hazard level parameters according to an embodiment of the present invention. Detailed Implementation

[0016] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0017] like Figure 1 As shown, an embodiment of the present invention provides a method for predicting typhoon storm surge hazard level parameters, including: Step 1: Obtain the target characteristic parameters of the current typhoon in the target area and the preset storm surge intensity level index comparison table for the target area; Step 2: Input the target feature parameters into the preset storm surge prediction model, and output the prediction result through the preset storm surge prediction model; wherein, the preset storm surge prediction model is determined by multiple sets of historical typhoon data of the current target area or according to a preset formula. The result is determined; where y is the output value of the preset storm surge prediction model. The landfall wind speed of the current typhoon is among the target characteristic parameters. The distance between the current typhoon landfall point and the target area is a characteristic parameter of the target. The target feature parameter is the current landfall speed of the typhoon. The wind speed in the target area currently being passed by the typhoon is one of the target feature parameters. The target feature parameter is the speed at which the typhoon moves through the target area. The distance between the current typhoon and the target area when they are at the same longitude is the target feature parameter. The target characteristic parameter is the air pressure in the area where the typhoon is currently passing through the target region; Step 3: Based on the prediction results and the preset storm surge intensity level index comparison table for the target area, determine the current storm surge hazard level parameter for the current target area.

[0018] In this embodiment, step 1, the target characteristic parameters of the current typhoon in the target area include at least one of the following: typhoon intensity characteristic parameters, scale characteristic parameters, movement speed characteristic parameters, angle characteristic parameters, and distance characteristic parameters; in specific use, the target characteristic parameters can be determined according to a preset storm surge prediction model, for example, by using the formula When used as a preset storm surge prediction model, the corresponding target characteristic parameters include: intensity characteristic parameters: the landfall wind speed of the current typhoon, the wind speed of the current typhoon passing through the target area, and the air pressure of the current typhoon passing through the target area; distance characteristic parameters: the distance between the landfall point of the current typhoon and the target area, and the distance between the current typhoon and the target area when they are at the same longitude; and movement speed characteristic parameters: the landfall movement speed of the current typhoon and the movement speed of the current typhoon passing through the target area. In this embodiment, the values ​​in the target characteristic parameters of the current typhoon are all forecast values ​​of the current typhoon obtained through meteorological data, that is, the target characteristic parameters of the current typhoon can be directly obtained through meteorological forecasts; the preset storm surge prediction model can be constructed in advance based on multiple sets of historical typhoon data of the current target area, and under extreme environmental conditions, the formula fitted by this invention can also be directly used. This can be used as a preset storm surge prediction model; the preset storm surge intensity level index comparison table for the target area can also be constructed according to needs, or the data in the preset storm surge intensity level index comparison table in Table 1 can be used directly. Table 1. Comparison Table of Preset Storm Surge Intensity Level Indices

[0019] In this embodiment, step 3, determining the current storm surge hazard level parameter of the target area based on the prediction results and the preset storm surge intensity level index comparison table for the target area, can specifically be achieved, for example, by using the calculation formula given in this scheme, when... , , , , , , If the calculated output value y of the preset storm surge prediction model is approximately 2.55 (the actual water level rise at the first tide observation station in the target area is 116 cm, and the water level rise at the second tide observation station is 93 cm, with an average of 104.5, corresponding to a level index of 3), then the current danger level prediction value is 2.55. This prediction result is then optimized by rounding to the nearest integer. The optimized value is then compared with the preset storm surge intensity level index table for the target area to determine the current storm surge in the target area. The danger index is calculated, for example, if the predicted result is 2.55, it is optimized to 3. Then, according to the preset storm surge intensity level index reference table for the target area, the predicted water increase range corresponding to the current target area when the level index is 3 is found (here, level 3 actually corresponds to a predicted result greater than 2.5 and less than 3.5). This is the predicted water increase parameter of the current typhoon storm surge for the current target area. The larger the value of the predicted result, the closer the corresponding predicted water increase parameter is to the maximum limit value of the current range, and vice versa. Based on this parameter, corresponding protective measures can be taken in advance.

[0020] The method for predicting typhoon storm surge hazard level parameters described in this invention enables non-professional groups to achieve real-time prediction of current regional storm surge hazard level parameters under extreme environments using simple computing devices or manual calculations. It also boasts advantages such as fast prediction speed and easy interpretation of prediction results. The extreme environments refer to situations where high-performance computers are unavailable or where computer computing power is limited. This method allows even non-professional groups to directly predict the storm surge hazard level parameters brought by a current typhoon, thereby facilitating preventative measures before the typhoon and rescue operations afterward.

[0021] In an optional embodiment of the present invention, obtaining a preset storm surge intensity level index lookup table for the target area in step 1 may include: Step 11: Obtain multiple sets of maximum water surge parameters during historical typhoon storm surges from the two tide level observation stations closest to the target area; Step 12: Determine the interval parameters for storm surge intensity levels based on the maximum water increase parameters during multiple sets of historical typhoon storm surge periods. Step 13: Determine the preset storm surge intensity level index reference table for the target area based on the interval parameters and the preset number of levels.

[0022] In this embodiment, when obtaining the maximum water increase parameters during multiple sets of historical typhoon storm surges in step 11, it is necessary to obtain at least one parameter data with a maximum water increase of more than 50cm from two tide level observation stations as valid data for statistical analysis. That is, at least one maximum water increase parameter in each set of historical typhoon storm surge parameters is greater than 50cm. For example, if the maximum water increase of the first tide level observation station is less than 50cm during a certain typhoon, then the current typhoon parameter can only be used for subsequent calculations in this scheme if the detected maximum water increase value of the second tide level observation station is greater than 50cm. Parameters during historical typhoon storm surges where the maximum water increase detected by both tide level observation stations is less than 50cm cannot be used as subsequent calculation parameters in this scheme. In this embodiment, step 12 determines the interval parameter for the storm surge intensity level based on the maximum water increase parameters during multiple sets of historical typhoon storm surges. Specifically, it can be done by determining the first parameter value of each set of maximum water increase parameters based on the maximum water increase parameters during each set of historical typhoon storm surges from two tide level observation stations. For example, if the maximum water increase at the first tide level observation station is 65cm and the maximum water increase at the second tide level observation station is 85cm during a certain typhoon, then the first parameter value of the current set of maximum water increase parameters is... Based on the first parameter value of the maximum water increase parameter in each group, the interval parameter of the storm surge intensity level is determined. Specifically, the first parameter values ​​of the maximum water increase parameters in all groups are added together and then divided by the total number of groups to obtain the second parameter value. For example, if there are 8 groups of data, the 8 groups of data are added together and then divided by 8. The second parameter value is used as the interval parameter of the storm surge intensity level. Step 13: Based on the interval parameter and the number of preset levels, determine the preset storm surge intensity level index reference table for the target area. Specifically, the number of preset levels is 5, starting from zero and divided into five levels from small to large using the interval parameter as the interval. For example, when the interval parameter is 60cm, it is divided into 5 levels with each 60cm interval as the interval. The water increase value range corresponding to the first level is 0-60cm, the water increase value range corresponding to the second level is 60-120cm, the water increase value range corresponding to the third level is 120-180cm, the water increase value range corresponding to the fourth level is 180-240cm, and the water increase value range corresponding to the fifth level is greater than 300cm.

[0023] In a preferred embodiment, the preset storm surge intensity level index comparison table for the target area can directly adopt the parameters in the preset storm surge intensity level index comparison table for the target area as shown in Table 1 above; Table 1 is a level classification table with an average water increase of 50cm as the interval.

[0024] In an optional embodiment of the present invention, step 2, which determines the preset storm surge prediction model based on multiple sets of historical typhoon data for the current target area, may include: Step 21: Obtain multiple sets of preset initial impact factors; wherein each set of preset initial impact factors includes at least five different initial impact factors; Step 22: Determine the storm surge intensity level corresponding to each set of historical typhoon data according to the preset storm surge intensity level index reference table for the target area; Step 23: Based on each set of historical typhoon data for the current target area and the storm surge intensity level corresponding to each set of historical typhoon data, determine the parameter value of each initial impact factor in each set of preset initial impact factors and the storm surge intensity level corresponding to each set of preset initial impact factors. Step 24: Based on the parameter values ​​of each initial impact factor in each set of preset initial impact factors and the storm surge intensity level corresponding to each set of preset initial impact factors, determine the correlation parameter value between each initial impact factor and the storm surge intensity level. Step 25: Determine the target impact factor of the prediction model based on the correlation parameter values ​​between each initial impact factor and the storm surge intensity level; Step 26: Determine the preset storm surge prediction model based on the target parameter factors.

[0025] In this embodiment, when the environmental conditions in the current target area permit, i.e., when there is an electronic device with certain computing capabilities, a preset storm surge prediction model that is more consistent with the current target area can be constructed based on the typhoon prediction parameters of the current target area to predict the current storm surge; wherein, each set of preset initial influencing factors in step 21 includes: typhoon landfall wind speed, the square of the typhoon landfall wind speed, typhoon landfall pressure, typhoon wind speed passing through the target area, the square of the typhoon wind speed passing through the target area, the pressure of the typhoon passing through the target area, and the radius of the 7-level wind circle of the typhoon passing through the target area. Radius of the 10-level wind circle passing through the target area of ​​the typhoon, typhoon landfall speed, square of typhoon landfall speed, typhoon speed passing through the target area, square of typhoon speed passing through the target area, typhoon landfall angle, sine of typhoon landfall angle, cosine of typhoon landfall angle, angle of movement of the typhoon passing through the target area, sine of typhoon movement angle, cosine of typhoon movement angle, distance from the typhoon landfall point to the target area, distance from the typhoon to the target area when the typhoon and the target area are at the same longitude, typhoon landfall wind speed divided by the distance from the typhoon landfall point to the target area, square of the typhoon landfall wind speed divided by the distance from the typhoon landfall point to the target area, typhoon landfall wind speed. The western component of the typhoon's speed divided by the distance from the landfall point to the target area; the northern component of the typhoon's landfall wind speed divided by the distance from the landfall point to the target area; the square of the typhoon's landfall speed divided by the distance from the landfall point to the target area; the square of the typhoon's wind speed over the target area divided by the distance from the typhoon to the target area; the wind speed over the target area divided by the distance from the typhoon to the target area; the western component of the typhoon's wind speed over the target area divided by the distance from the typhoon to the target area. The initial influencing factors are at least five different factors, including: the distance of the typhoon from the target area, the northern component of the typhoon's wind speed over the target area divided by the distance of the typhoon from the target area, the typhoon's speed over the target area divided by the distance of the typhoon from the target area, the square of the typhoon's speed over the target area divided by the distance of the typhoon from the target area, the western component of the typhoon's speed over the target area divided by the distance of the typhoon from the target area, the northern component of the typhoon's speed over the target area divided by the distance of the typhoon from the target area, the radius of the 7-level wind circle of the typhoon over the target area divided by the distance of the typhoon from the target area, and the radius of the 10-level wind circle of the typhoon over the target area divided by the distance of the typhoon from the target area. In this embodiment, step 23 determines the parameter values ​​of each initial impact factor in each set of preset initial impact factors and the storm surge intensity level corresponding to each set of historical typhoon data for the current target area. Specifically, each set of historical typhoon data corresponds to a set of preset initial impact factors. Based on the specific parameters of each set of historical typhoon data, the specific value of each initial impact factor and the corresponding storm surge intensity level in each set of preset initial impact factors are determined. For example, the parameter value of the typhoon landfall wind speed factor in the first set of preset initial impact factors is directly determined based on the typhoon landfall wind speed in the first set of historical typhoon data. The square factor of the typhoon landfall wind speed can be obtained by squaring the typhoon landfall wind speed in the first set of historical typhoon data. The storm surge intensity levels of the typhoon landfall wind speed factor and the square factor of the typhoon landfall wind speed are both directly adopted from the storm surge intensity levels of the first set of historical typhoon data.

[0026] In an optional embodiment of the present invention, step 22, which determines the storm surge intensity level corresponding to each set of historical typhoon data based on a preset storm surge intensity level index lookup table for the target area, may include: Step 221: Obtain the first maximum water increase and the second maximum water increase corresponding to the two tide level observation stations closest to the target area during each historical typhoon. Step 222: Determine the storm surge intensity level corresponding to each set of historical typhoon data based on the first maximum water increase, the second maximum water increase, and the preset storm surge intensity level index comparison table for the target area.

[0027] In this embodiment, a set of historical typhoon data corresponds to one historical typhoon. Based on the first maximum water level rise, the second maximum water level rise, and a preset storm surge intensity index reference table for the target area corresponding to each set of historical typhoon data, the storm surge intensity level corresponding to each set of historical typhoon data is determined. Specifically, the average maximum water level rise of the first and second maximum water level rises is first calculated. For example, assuming that in a certain historical typhoon, the maximum water level rise at the first tide level observation station is 65cm and the maximum water level rise at the second tide level observation station is 85cm, then the average maximum water level rise of the historical typhoon data corresponding to the current historical typhoon is... Then it is Based on the calculated average maximum water increase, the corresponding level is determined by referring to the preset storm surge intensity level index reference table for the target area. For example, assuming the preset storm surge intensity level index reference table for the target area is as shown in Table 1 above, then it can be seen from Table 1 that the average maximum water increase of 75 cm is between 50 cm and 100 cm, and the storm surge intensity level corresponding to the current range is level 2. Therefore, the storm surge intensity level corresponding to the current historical typhoon data is level 2.

[0028] In an optional embodiment of the present invention, step 24, determining the correlation parameter value between each initial impact factor and the storm surge intensity level based on the parameter value of each initial impact factor in each set of preset initial impact factors and the storm surge intensity level corresponding to each set of preset initial impact factors, may include: Through formula Determine the correlation parameter values ​​between each initial influencing factor and the storm surge intensity level; in, This represents the correlation parameter value between the j-th initial influencing factor and the storm surge intensity level; n represents the number of preset initial influencing factors. This represents the parameter value of the j-th initial impact factor in the i-th group of preset initial impact factors; This represents the storm surge intensity level value corresponding to the j-th initial impact factor in the i-th group of preset initial impact factors; This represents the average value of all j-th initial influence factor parameters; This represents the average storm surge intensity level value of all j-th initial influencing factors.

[0029] In this embodiment, the average value corresponding to the j-th initial impact factor is obtained by adding the values ​​of the j-th initial impact factor in all groups of preset initial impact factors and dividing by the total number of groups. In this embodiment, the correlation parameter value corresponding to each initial impact factor can be calculated by the above formula, as shown in Table 2, which is a correlation parameter table between storm surge intensity level and initial impact factor. Table 2. Correlation between Storm Surge Index and Typhoon Parameter Factors

[0030] In an optional embodiment of the present invention, step 25, which determines the target impact factor of the prediction model based on the correlation parameter value between each initial impact factor and the storm surge intensity level, may include: Step 251: Based on the correlation parameter values ​​between each initial impact factor and the storm surge intensity level, the initial impact factors are screened for the first time using a first preset value and a first preset rule to obtain the first impact factor. Step 252: Based on the preset number of target impact factors and the correlation value of the first impact factor, perform a second screening process on the first impact factor to obtain the target parameter factors of the prediction model.

[0031] In this embodiment, the first preset value can be 0.4. The first preset rule is to retain only the initial influencing factors whose absolute value of the correlation parameter is greater than the first preset value, and the categories of each initial influencing factor retained are different. That is, the selected target parameter factors cannot have the same type of influencing factors. Each influencing factor represents a category. For influencing factors of the same category, the influencing factor corresponding to the maximum value of the correlation parameter is retained. For example, the typhoon landfall wind speed factor and the square factor of the typhoon landfall wind speed are two different influencing factors, but they are the same type of influencing factors. Both of them are influenced by the typhoon landfall wind speed. Therefore, only one of them can be retained. The correlation parameter values ​​of the two are directly compared, and the influencing factor corresponding to the maximum absolute value of the correlation parameter is retained.

[0032] In this embodiment, the preset number is 5; based on the preset number of target impact factors and the correlation value of the first impact factors, the first impact factors are subjected to a second screening process to obtain the target parameter factors of the prediction model. Specifically, the correlation values ​​of all the first impact factors are compared, and the five with the largest values ​​are selected as the target parameter factors of the prediction model.

[0033] In an optional embodiment of the present invention, step 26, determining a preset storm surge prediction model based on the target parameter factor, may include: Based on the correlation parameter values ​​of the target parameter factors, the obtained preset number of target influence factors are sorted from largest to smallest, and then processed using the formula... Determine the preset storm surge prediction model; Where x1 is the first target impact factor after ranking; x2 is the second target impact factor after ranking; x3 is the third target impact factor after ranking; x4 is the fourth target impact factor after ranking; and x5 is the fifth target impact factor after ranking.

[0034] In this embodiment, determining the preset storm surge prediction model based on the target parameter factors specifically involves: sorting the five target influence factors from largest to smallest based on the absolute values ​​of their correlation parameter values; then, using the target influence factor corresponding to the largest correlation parameter value as the first target influence factor, and the target influence factor corresponding to the smallest correlation parameter value as the fifth target influence factor, and so on, according to the magnitude of the correlation parameter values. For example, in Table 2 above, the first target influence factor is the square of the typhoon landfall wind speed divided by the distance from the landfall point to the target area; the second target influence factor is the typhoon landfall distance... The first objective factor is the square of the typhoon's speed over the target area; the second objective factor is the typhoon's speed over the target area divided by the distance between the typhoon and the target area; the third objective factor is the typhoon's air pressure over the target area. Based on the parameters in the corresponding objective factors, the target characteristic parameters of the typhoon to be predicted for the target area can be determined as follows: the typhoon's landfall wind speed, the distance between the typhoon's landfall point and the target area, the typhoon's landfall speed, the typhoon's wind speed over the target area, the typhoon's speed over the target area, the distance between the typhoon and the target area when they are at the same longitude, and the air pressure over the target area.

[0035] like Figure 2 As shown, embodiments of the present invention also provide a device 20 for predicting typhoon storm surge hazard level parameters, comprising: The acquisition module 201 is used to acquire the target characteristic parameters of the current typhoon in the target area and the preset storm surge intensity level index comparison table of the target area; Processing module 202 is used to input the target feature parameters into a preset storm surge prediction model and output the prediction result through the preset storm surge prediction model; wherein, the preset storm surge prediction model is determined by multiple sets of historical typhoon data of the current target area or according to a preset formula. The result is determined; where y is the output value of the preset storm surge prediction model. The landfall wind speed of the current typhoon is among the target characteristic parameters. The distance between the current typhoon landfall point and the target area is a characteristic parameter of the target. The target feature parameter is the current landfall speed of the typhoon. The wind speed in the target area currently being passed by the typhoon is one of the target feature parameters. The target feature parameter is the speed at which the typhoon moves through the target area. The distance between the current typhoon and the target area when they are at the same longitude is the target feature parameter. The air pressure in the target area where the typhoon is currently passing is used as a target characteristic parameter; based on the prediction results and the preset storm surge intensity level index comparison table for the target area, the current storm surge hazard level parameter for the current target area is determined.

[0036] Optionally, obtain a preset storm surge intensity level index reference table for the target area, including: Obtain multiple sets of maximum water surge parameters during historical typhoon storm surges from the two tide level observation stations closest to the target area; Based on the maximum water increase parameters during multiple sets of historical typhoon storm surges, the interval parameters for storm surge intensity levels were determined. Based on the interval parameters and the number of preset levels, a preset storm surge intensity level index comparison table for the target area is determined.

[0037] Optionally, based on multiple sets of historical typhoon data for the current target area, the preset storm surge prediction model is determined, including: Obtain multiple sets of preset initial impact factors; wherein each set of preset initial impact factors includes at least five different initial impact factors; Based on the preset storm surge intensity index comparison table for the target area, determine the storm surge intensity level corresponding to each set of historical typhoon data; Based on each set of historical typhoon data for the current target area and the storm surge intensity level corresponding to each set of historical typhoon data, determine the parameter values ​​of each initial impact factor in each set of preset initial impact factors and the storm surge intensity level corresponding to each set of preset initial impact factors. Based on the parameter values ​​of each initial impact factor in each set of preset initial impact factors and the storm surge intensity level corresponding to each set of preset initial impact factors, determine the correlation parameter value between each initial impact factor and the storm surge intensity level; The target impact factor of the prediction model is determined based on the correlation parameter values ​​between each initial impact factor and the storm surge intensity level. Based on the target parameter factors, a preset storm surge prediction model is determined.

[0038] Optionally, based on a preset storm surge intensity index reference table for the target area, determine the storm surge intensity level corresponding to each set of historical typhoon data, including: Obtain the first and second maximum water level increases corresponding to the two tide level observation stations closest to the target area during each historical typhoon period; Based on the first maximum water increase, the second maximum water increase, and the preset storm surge intensity index of the target area corresponding to each set of historical typhoon data, the storm surge intensity level corresponding to each set of historical typhoon data is determined.

[0039] Optionally, based on the parameter values ​​of each initial impact factor in each set of preset initial impact factors and the storm surge intensity level corresponding to each set of preset initial impact factors, determine the correlation parameter value between each initial impact factor and the storm surge intensity level, including: Through formula Determine the correlation parameter values ​​between each initial influencing factor and the storm surge intensity level; in, This represents the correlation parameter value between the j-th initial influencing factor and the storm surge intensity level; n represents the number of preset initial influencing factors. This represents the parameter value of the j-th initial impact factor in the i-th group of preset initial impact factors; This represents the storm surge intensity level value corresponding to the j-th initial impact factor in the i-th group of preset initial impact factors; This represents the average value of all j-th initial influence factor parameters; This represents the average storm surge intensity level value of all j-th initial influencing factors.

[0040] Optionally, based on the correlation parameter values ​​between each initial impact factor and the storm surge intensity level, the target impact factors of the prediction model are determined, including: Based on the correlation parameter values ​​between each initial impact factor and the storm surge intensity level, the initial impact factors are subjected to a first screening process using a first preset value and a first preset rule to obtain the first impact factor. Based on the preset number of target impact factors and the correlation value of the first impact factor, the first impact factor is subjected to a second screening process to obtain the target parameter factors of the prediction model.

[0041] Optionally, a preset storm surge prediction model is determined based on the target parameter factors, including: Based on the correlation parameter values ​​of the target parameter factors, the obtained preset number of target influence factors are sorted from largest to smallest, and then processed using the formula... Determine the preset storm surge prediction model; Where x1 is the first target impact factor after ranking; x2 is the second target impact factor after ranking; x3 is the third target impact factor after ranking; x4 is the fourth target impact factor after ranking; and x5 is the fifth target impact factor after ranking.

[0042] It should be noted that this device is the same as the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0043] Embodiments of the present invention also provide a computing device, including: a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the method described above.

[0044] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0045] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0046] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0047] In the embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0048] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0049] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0050] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0051] Furthermore, it should be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of the present invention. Moreover, the steps performing the above series of processes can naturally be executed in the order described, but are not necessarily required to be executed in chronological order; some steps can be executed in parallel or independently of each other. Those skilled in the art will understand that all or any step or component of the method and apparatus of the present invention can be implemented in any computing device (including processors, storage media, etc.) or network of computing devices, in hardware, firmware, software, or a combination thereof. This is something that those skilled in the art can achieve by using their basic programming skills after reading the description of the present invention.

[0052] Therefore, the object of the present invention can also be achieved by running a program or a set of programs on any computing device. The computing device can be a known general-purpose device. Therefore, the object of the present invention can also be achieved simply by providing a program product containing program code implementing the method or apparatus. That is, such a program product also constitutes the present invention, and the storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any known storage medium or any storage medium developed in the future. It should also be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent to the present invention. Furthermore, the steps performing the above series of processes can naturally be performed in the order described, but are not necessarily required to be performed in chronological order. Some steps can be performed in parallel or independently of each other.

[0053] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for predicting storm surge hazard level parameters for typhoons, characterized in that, include: Obtain the target characteristic parameters of the current typhoon in the target area and the reference table of the preset storm surge intensity level index of the target area; The target feature parameters are input into a preset storm surge prediction model, and the prediction results are output through the preset storm surge prediction model; wherein, the preset storm surge prediction model is determined by multiple sets of historical typhoon data for the current target area; Based on the prediction results and the preset storm surge intensity level index comparison table for the target area, the current storm surge hazard level parameter for the current target area is determined.

2. The method for predicting typhoon storm surge hazard level parameters according to claim 1, characterized in that, Obtain a preset storm surge intensity level index reference table for the target area, including: Obtain multiple sets of maximum water surge parameters during historical typhoon storm surges from the two tide level observation stations closest to the target area; Based on the maximum water increase parameters during multiple sets of historical typhoon storm surges, the interval parameters for storm surge intensity levels were determined. Based on the interval parameters and the number of preset levels, a preset storm surge intensity level index comparison table for the target area is determined.

3. The method for predicting the storm surge hazard index of typhoons according to claim 1, characterized in that, Based on multiple sets of historical typhoon data for the current target area, the preset storm surge prediction model is determined, including: Obtain multiple sets of preset initial impact factors; wherein each set of preset initial impact factors includes at least five different initial impact factors; Based on the preset storm surge intensity index comparison table for the target area, determine the storm surge intensity level corresponding to each set of historical typhoon data; Based on each set of historical typhoon data for the current target area and the storm surge intensity level corresponding to each set of historical typhoon data, determine the parameter values ​​of each initial impact factor in each set of preset initial impact factors and the storm surge intensity level corresponding to each set of preset initial impact factors. Based on the parameter values ​​of each initial impact factor in each set of preset initial impact factors and the storm surge intensity level corresponding to each set of preset initial impact factors, determine the correlation parameter value between each initial impact factor and the storm surge intensity level; The target impact factor of the prediction model is determined based on the correlation parameter values ​​between each initial impact factor and the storm surge intensity level. Based on the target parameter factors, a preset storm surge prediction model is determined.

4. The method for predicting typhoon storm surge hazard level parameters according to claim 3, characterized in that, Based on the preset storm surge intensity index reference table for the target area, determine the storm surge intensity level corresponding to each set of historical typhoon data, including: Obtain the first and second maximum water level increases corresponding to the two tide level observation stations closest to the target area during each historical typhoon period; Based on the first maximum water increase, the second maximum water increase, and the preset storm surge intensity index of the target area corresponding to each set of historical typhoon data, the storm surge intensity level corresponding to each set of historical typhoon data is determined.

5. The method for predicting typhoon storm surge hazard level parameters according to claim 3, characterized in that, Based on the parameter values ​​of each initial impact factor in each set of preset initial impact factors and the storm surge intensity level corresponding to each set of preset initial impact factors, determine the correlation parameter values ​​between each initial impact factor and the storm surge intensity level, including: Through formula Determine the correlation parameter values ​​between each initial influencing factor and the storm surge intensity level; in, This represents the correlation parameter value between the j-th initial influencing factor and the storm surge intensity level; n represents the number of preset initial influencing factors. This represents the parameter value of the j-th initial impact factor in the i-th group of preset initial impact factors; This represents the storm surge intensity level value corresponding to the j-th initial impact factor in the i-th group of preset initial impact factors; This represents the average value of all j-th initial influence factor parameters; This represents the average storm surge intensity level value of all j-th initial influencing factors.

6. The method for predicting typhoon storm surge hazard level parameters according to claim 3, characterized in that, Based on the correlation parameter values ​​between each initial impact factor and the storm surge intensity level, the target impact factors for the prediction model are determined, including: Based on the correlation parameter values ​​between each initial impact factor and the storm surge intensity level, the initial impact factors are first screened using a first preset value and a first preset rule to obtain the first impact factor. Based on the preset number of target impact factors and the correlation value of the first impact factor, the first impact factor is subjected to a second screening process to obtain the target parameter factors of the prediction model.

7. The method for predicting typhoon storm surge hazard level parameters according to claim 3, characterized in that, Based on the target parameter factors, a preset storm surge prediction model is determined, including: Based on the correlation parameter values ​​of the target parameter factors, the obtained preset number of target influence factors are sorted from largest to smallest, and then processed using the formula... Determine the preset storm surge prediction model; Where x1 is the first target impact factor after ranking; x2 is the second target impact factor after ranking; x3 is the third target impact factor after ranking; x4 is the fourth target impact factor after ranking; and x5 is the fifth target impact factor after ranking.

8. A device for predicting typhoon storm surge hazard level parameters, characterized in that, include: The acquisition module is used to acquire the target characteristic parameters of the current typhoon in the target area and the preset storm surge intensity level index comparison table of the target area; The processing module is used to input the target feature parameters into a preset storm surge prediction model and output the prediction results through the preset storm surge prediction model; wherein, the preset storm surge prediction model is determined by multiple sets of historical typhoon data of the current target area; and the current storm surge hazard level parameters of the current target area are determined according to the prediction results and the preset storm surge intensity level index comparison table of the target area.

9. A computing device, characterized in that, include: A processor, a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, include: A storage instruction that, when executed on a computer, causes the computer to perform the method as described in any one of claims 1 to 7.

Images