A method and apparatus for evaluating wave models

Abstract

This application provides a method and apparatus for evaluating wave models. By differentiating the parameter values ​​of a general wave model, multiple candidate wave models with varying parameter values ​​are obtained. Each candidate wave model is then tested, and the candidate wave model with the smallest error relative to the actual wave conditions of the target sea area is selected as the wave model suitable for that target sea area. Specifically, the candidate wave model with the smallest error relative to the actual wave conditions of the target sea area simulates the wave conditions of that area more closely, and the candidate wave model corresponding to this parameter combination performs better for the target sea area. Thus, this application provides a wave model that more closely resembles the actual wave conditions of the target sea area, facilitating subsequent wave simulation of that area.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of resource utilization, and in particular to a wave model evaluation method and device. BACKGROUND

[0002] To establish a long-time wave element database in the deep sea area of Shanghai, MIKE 21 SW wave model can be used to perform numerical simulation calculation of waves in the East China Sea. MIKE 21 SW is developed by the Danish Hydraulic Institute (DHI), and since its development, the model has absorbed a large amount of application experience from projects worldwide, and has been widely used and continuously developed in international river estuary, coastal and marine engineering design. SUMMARY

[0003] The present application shows a wave model evaluation method and device.

[0004] In a first aspect, the present application shows a wave model evaluation method, which comprises:

[0005] determining a plurality of types of parameters in a general wave model;

[0006] for any one type of parameter, determining a plurality of candidate values of the type of parameter;

[0007] obtaining a plurality of parameter combinations, each parameter combination including a candidate value of each type of parameter; at least one candidate value of the same type of parameter in any two parameter combinations is different;

[0008] for any one parameter combination, setting the parameters of each type in the general wave model according to the candidate value of each type of parameter in the parameter combination, to obtain a candidate wave model corresponding to the parameter combination; obtaining at least one type of wave index simulated by the candidate wave model corresponding to the parameter combination; obtaining actual at least one type of wave index of a target sea area; according to the at least one type of wave index simulated by the candidate wave model corresponding to the parameter combination and the actual at least one type of wave index of the target sea area, obtaining an error index of the candidate wave model corresponding to the parameter combination;

[0009] determining the candidate wave model with the lowest error index as the wave model suitable for the target sea area.

[0010] In a second aspect, the present application shows a wave model evaluation device, which comprises:

[0011] a first determination module configured to determine a plurality of types of parameters in a general wave model;

[0012] The second determining module is used to determine multiple candidate values ​​of the parameter of any type.

[0013] The first acquisition module is used to acquire multiple parameter combinations, each parameter combination including a candidate value of a parameter of each type; at least one parameter of the same type in any two parameter combinations has different candidate values;

[0014] The setting module is used to set the parameters of each type in the general wave model according to a candidate value of each type of parameter in the parameter combination for any parameter combination, so as to obtain the candidate wave model corresponding to the parameter combination; the second acquisition module is used to acquire at least one type of wave index simulated by the candidate wave model corresponding to the parameter combination; the third acquisition module is used to acquire at least one type of actual wave index of the target sea area; the fourth acquisition module is used to acquire the error index of the candidate wave model corresponding to the parameter combination based on at least one type of wave index simulated by the candidate wave model corresponding to the parameter combination and at least one type of actual wave index of the target sea area.

[0015] The third determination module is used to determine the candidate wave model with the lowest error index as the wave model suitable for the target sea area.

[0016] Thirdly, this application discloses an electronic device comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to perform the method as described in any of the preceding aspects.

[0017] Fourthly, this application discloses a non-transitory computer-readable storage medium in which, when the instructions in the storage medium are executed by a processor of an electronic device, enable the electronic device to perform the methods described in any of the preceding aspects.

[0018] Fifthly, this application discloses a computer program product in which, when the instructions in the computer program product are executed by a processor of an electronic device, the electronic device is enabled to perform the method described in any of the preceding aspects.

[0019] The technical solution provided in this application may include the following beneficial effects:

[0020] This application utilizes differentiated parameter settings on a general wave model to obtain multiple candidate wave models with varying parameter values. Each candidate model is then tested, and the model with the smallest error relative to the actual wave conditions in the target sea area is selected as the applicable wave model for that area. The candidate wave model with the smallest error closely simulates the actual wave conditions in the target sea area, and the candidate wave model corresponding to this parameter combination performs better for that area. Thus, this application provides a wave model that more closely resembles the actual wave conditions in the target sea area, facilitating subsequent wave simulation in that region. Attached Figure Description

[0021] Figure 1 This is a flowchart of the steps of an evaluation method for a wave model according to this application.

[0022] Figure 2 This is a structural block diagram of an evaluation device for a wave model according to this application.

[0023] Figure 3 This is a block diagram of an electronic device according to this application.

[0024] Figure 4 This is a block diagram of an electronic device according to this application. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] The MIKE 21 SW wave model is a general-purpose model used to simulate waves. However, the specific conditions in different sea areas around the world are different, and the actual wave conditions in different sea areas are also different. The MIKE 21 SW wave model is not derived from the actual wave conditions of a specific sea area.

[0027] Therefore, for any specific sea area, the wave conditions simulated by the MIKE 21 SW wave model do not perfectly match the actual wave conditions in that specific sea area. Thus, the MIKE 21 SW wave model cannot accurately simulate and simulate the wave conditions in a specific sea area.

[0028] Therefore, how to obtain a wave model that can accurately simulate the actual situation of waves in a specific sea area is a technical problem that urgently needs to be solved.

[0029] Reference Figure 1 The diagram illustrates a flowchart of a wave model evaluation method according to this application. This method can be applied to electronic devices, which may include terminals or servers, etc. Specifically, the method may include the following steps:

[0030] In step S101, parameters for multiple types in the general wave model are determined.

[0031] In this application, the general wave model may include: MIKE 21 SW module.

[0032] The physical phenomena considered in the MIKE 21 SW wave model include: wind-driven waves, nonlinear interactions between waves, energy loss caused by white caps, energy loss caused by bottom friction, energy loss caused by wave breaking due to water depth changes, wave reflection, diffraction and shallow water deformation, wave-current interaction, water depth changes and the effects of wet and dry zones.

[0033] The wave model is based on the wave action conservation equation and uses the wave action density N(σ, θ) to describe the wave. The independent variables of the model are the relative wave frequency σ and the wave direction θ. The relationship between the wave action density and the wave energy spectrum density E(σ, θ) is as follows:

[0034] N(σ,θ)=E(σ,θ) / σ

[0035] Where σ is the relative frequency and θ is the wave direction.

[0036] In the Cartesian coordinate system, the governing equations of the wave model, i.e., the wave action conservation equations, can be expressed as:

[0037]

[0038] in Group velocity, To find the gradient, Cx and Cy represent the changes in wave propagation in geographic space (x, y), respectively, and Cσ represents the change in relative frequency caused by changes in water depth and current. θ This represents refraction caused by water depth and current. S refers to the source function expressed as spectral density in the energy balance equation. The propagation velocities in the equations are all calculated using linear wave theory.

[0039]

[0040]

[0041]

[0042]

[0043] d represents the water depth; For flow rate, ;k = (k x k y ) represents the wave number; s represents the spatial coordinate along the θ direction; m represents the coordinate perpendicular to s, and c g This represents the change as the wave propagates along the direction of gravity.

[0044] In spherical coordinates:

[0045] dσdθdødλ=Ndσdθdxdy

[0046]

[0047] R is the Earth's radius, ø is latitude, and λ is longitude.

[0048] The form of the wave conservation equation is:

[0049]

[0050] in For the overall source function:

[0051]

[0052] The source function term in the wave model describes the superposition of source functions for various physical phenomena:

[0053] S=Sin+Snl+Sds+Sbot+Ssurf

[0054] S refers to the total energy value, Sin refers to the energy input by the wind, Snl refers to the energy loss caused by the nonlinear interaction between waves, Sds refers to the energy loss caused by the white cap, Sbot refers to the energy loss caused by bottom friction, and Ssurf refers to the energy loss caused by wave breaking due to changes in water depth.

[0055] The main dynamic conditions for wave models are: wind fields that vary with space and time. Wave generation, growth, and decay are related to the three elements of wind and waves: wind speed, wind duration, and wind area. Accurate wind field input is crucial for the accuracy of wave simulation. To simulate the complete growth process of wind and waves, the wind area of ​​the wave model needs to be large enough to account for open-sea swells even when wave spectral boundary information is missing.

[0056] In step S102, for any type of parameter, multiple candidate values ​​for that type of parameter are determined.

[0057] The same applies to each other type of parameter. This results in multiple candidate values ​​for each type of parameter.

[0058] In one embodiment, the parameter of this type is the energy loss caused by bottom friction. Thus, when determining multiple candidate values ​​for this type of parameter, the water depth of the target sea area can be determined. Multiple values ​​for bottom friction are set according to the water depth of the target sea area. For example, if the water depth of the target sea area is less than a preset water depth, the value of bottom friction is set to 0.02. Or, if the water depth of the target sea area is greater than or equal to the preset water depth, the value of bottom friction is set to 0.03. For any set value of bottom friction, the energy loss caused by bottom friction is calculated based on that value (the specific calculation method can be any existing calculation method, which will not be detailed here, and no specific calculation method is limited), obtaining the energy loss caused by bottom friction corresponding to that value. The energy loss caused by bottom friction corresponding to each value is then set as a candidate value for the parameter of this type.

[0059] Alternatively, in another embodiment, the parameter of this type is the energy loss caused by the nonlinear interaction between waves. Thus, when determining multiple candidate values ​​for this type of parameter, the wind period of the target sea area can be determined. The coupling between wind and waves is set according to the wind period of the target sea area. Coupling includes coupling and non-coupling. For example, if the wind period of the target sea area is less than a preset period, the wind and waves are set to be uncoupled. Or, if the wind period of the target sea area is greater than a preset period, the wind and waves are set to be coupled. The energy loss caused by the nonlinear interaction between waves is calculated based on the coupling between wind and waves (the specific calculation method can be any existing calculation method, which will not be detailed here, and no specific calculation method is limited). The calculated energy loss caused by bottom friction is set as multiple candidate values ​​for this type of parameter.

[0060] In another embodiment, the parameters affecting wave height and period are mainly divided into wind input energy. The increase of the white hat input parameter Cdis leads to an increase in the wave height value, with a variation range of 1.4-4.0. The increase of Ddis leads to a decrease in the period, with a variation range of 0-1.

[0061] Increasing bottom friction Kn leads to a decrease in wave height, which is especially applicable to sea areas with a water depth of less than 20m, in the range of 0-1.

[0062] Selecting the air-sea coupling option strengthens the interaction between wind and waves, resulting in an increase in wave height after coupling.

[0063] This embodiment allows for the initial screening of parameters within a small range based on actual conditions. Parameters are then assigned values ​​within this small range, while values ​​are not assigned outside of it. This reduces the number of wave models that need to be set and improves the efficiency of obtaining wave models suitable for the target sea area.

[0064] In step S103, multiple parameter combinations are obtained, each parameter combination including a candidate value for a parameter of each type. At least one candidate value for a parameter of the same type in any two parameter combinations is different.

[0065] In step S104, for any parameter combination, the parameters of each type in the general wave model are set according to a candidate value of each type of parameter in the parameter combination to obtain the candidate wave model corresponding to the parameter combination. At least one type of wave index simulated by the candidate wave model corresponding to the parameter combination is obtained. At least one type of wave index of the actual target sea area is obtained. Based on the at least one type of wave index simulated by the candidate wave model corresponding to the parameter combination and the at least one type of wave index of the actual target sea area, the error index of the candidate wave model corresponding to the parameter combination is obtained.

[0066] In one embodiment of this application, when obtaining at least one type of wave index simulated by the candidate wave model corresponding to the parameter combination, the effective wave height of the wave simulated by the candidate wave model corresponding to the parameter combination can be obtained. And / or, the maximum wave height of the wave simulated by the candidate wave model corresponding to the parameter combination can be obtained. And / or, the spectral peak period of the wave simulated by the candidate wave model corresponding to the parameter combination can be obtained. And / or, the average period of the wave simulated by the candidate wave model corresponding to the parameter combination can be obtained. And / or, the zero-crossing period of the wave simulated by the candidate wave model corresponding to the parameter combination can be obtained.

[0067] In one embodiment, when obtaining the effective wave height of the wave simulated by the candidate wave model corresponding to the parameter combination, the zero-order momentum of the wave simulated by the candidate wave model corresponding to the parameter combination can be obtained. Based on the zero-order momentum, the effective wave height of the wave simulated by the candidate wave model corresponding to the parameter combination is calculated according to the following formula:

[0068]

[0069] Where m0 is the zero-order momentum of the wave simulated by the candidate wave model corresponding to this parameter combination, and H m0 The effective wave height is the simulated wave height of the candidate wave model corresponding to this parameter combination.

[0070] In another embodiment, when obtaining the maximum wave height of the wave simulated by the candidate wave model corresponding to the parameter combination, the maximum wave height Hmax of the wave simulated by the candidate wave model corresponding to the parameter combination can be calculated as follows:

[0071]

[0072] It is determined by assuming that the waves follow a Rayleigh distribution.

[0073]

[0074] Where N is the number of waves, N = duration / T 01 T 01 The average period of the waves simulated by the candidate wave model corresponding to this parameter combination is typically set to 3 hours (10800 seconds), H m0 The effective wave height is the simulated wave height of the candidate wave model corresponding to this parameter combination.

[0075] It is determined by assuming that the wave is a single wave.

[0076]

[0077]

[0078] k is the wave number corresponding to the period of the spectral peak, and d is the water depth.

[0079] It refers to the breaking wave height under deep-water conditions.

[0080] and The smaller of the two values ​​is taken as the maximum wave height.

[0081] In another embodiment, when obtaining the spectral peak period of the wave simulated by the candidate wave model corresponding to the parameter combination, the spectral peak period of the wave simulated by the candidate wave model corresponding to the parameter combination can be calculated by the following formula:

[0082]

[0083] Tp is the spectral peak period of the wave simulated by the candidate wave model corresponding to this parameter combination.

[0084] The spectral peak frequency fp is calculated by parabolic fitting between the peaks of the one-dimensional spectrum.

[0085] The steps for calculating the spectral peak frequency fp are as follows:

[0086] Find the exponent ip corresponding to the maximum spectral density in the one-dimensional spectrum.

[0087] make , , .

[0088] So that f0 = f(i) p -1), f1=f(i p ), f2=f(i p +1).

[0089] E0=E(i p -1), E1=E(i p ), E2=E(i p +1).

[0090] Thus, the spectral peak frequency can be calculated as follows:

[0091]

[0092]

[0093]

[0094] In another embodiment, when obtaining the average period of the waves simulated by the candidate wave model corresponding to the parameter combination, the average period T01 of the waves simulated by the candidate wave model corresponding to the parameter combination can be calculated by the following formula:

[0095]

[0096] m0 is the zero-order momentum of the wave simulated by the candidate wave model corresponding to this parameter combination, and m1 is the first-order momentum of the wave simulated by the candidate wave model corresponding to this parameter combination.

[0097] In another embodiment, when obtaining the zero-crossing period of the wave simulated by the candidate wave model corresponding to the parameter combination, the zero-crossing period T of the wave simulated by the candidate wave model corresponding to the parameter combination can be calculated by the following formula. 02 :

[0098]

[0099] m0 is the zero-order momentum of the wave simulated by the candidate wave model corresponding to this parameter combination, and m2 is the second-order momentum of the wave simulated by the candidate wave model corresponding to this parameter combination.

[0100] Accordingly, when obtaining at least one type of wave indicator for the target sea area, the effective wave height of the actual waves in the target sea area can be obtained. And / or, the maximum wave height of the actual waves in the target sea area can be obtained. And / or, the spectral peak period of the actual waves in the target sea area can be obtained. And / or, the average period of the actual waves in the target sea area can be obtained. And / or, the zero-crossing period of the actual waves in the target sea area can be obtained.

[0101] The aforementioned actual data may be obtained through satellite remote sensing data or through other actual monitoring equipment (such as monitoring sensors). This application does not limit the specific method of obtaining the actual data.

[0102] Accordingly, when obtaining the error index of the candidate wave model corresponding to the parameter combination, the square of the difference between the effective wave height of the wave simulated by the candidate wave model corresponding to the parameter combination and the effective wave height of the actual wave in the target sea area can be calculated and used as the error index of the candidate wave model corresponding to the parameter combination.

[0103] And / or, calculate the square of the difference between the maximum wave height simulated by the candidate wave model corresponding to the parameter combination and the maximum wave height of the actual waves in the target sea area, and use it as the error index of the candidate wave model corresponding to the parameter combination.

[0104] And / or, calculate the square of the difference between the peak period of the waves simulated by the candidate wave model corresponding to the parameter combination and the peak period of the actual waves in the target sea area, and use it as the error index of the candidate wave model corresponding to the parameter combination.

[0105] And / or, calculate the square of the difference between the average period of the waves simulated by the candidate wave model corresponding to the parameter combination and the average period of the actual waves in the target sea area, and use it as the error index of the candidate wave model corresponding to the parameter combination.

[0106] And / or, calculate the square of the difference between the zero-crossing period of the waves simulated by the candidate wave model corresponding to the parameter combination and the zero-crossing period of the actual waves in the target sea area, and use it as the error index of the candidate wave model corresponding to the parameter combination.

[0107] In this embodiment, the smaller the error index value of the candidate wave model corresponding to the parameter combination, the closer the simulated wave situation of the target sea area is to the actual wave situation of the target sea area, and the better the performance of the candidate wave model corresponding to the parameter combination for the target sea area.

[0108] The same applies to each other parameter combination, thus obtaining the error index of the candidate wave model corresponding to each parameter combination.

[0109] In step S105, the candidate wave model with the lowest error index is determined as the wave model suitable for the target sea area.

[0110] The candidate wave models can be sorted in order of their respective error indices from low to high, and then the candidate wave model ranked first can be selected as the wave model applicable to the target sea area.

[0111] This application utilizes differentiated parameter settings on a general wave model to obtain multiple candidate wave models with varying parameter values. Each candidate model is then tested, and the model with the smallest error relative to the actual wave conditions in the target sea area is selected as the applicable wave model for that area. The candidate wave model with the smallest error closely simulates the actual wave conditions in the target sea area, and the candidate wave model corresponding to this parameter combination performs better for that area. Thus, this application provides a wave model that more closely resembles the actual wave conditions in the target sea area, facilitating subsequent wave simulation in that region.

[0112] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions involved are not necessarily required by this application.

[0113] Reference Figure 2 The diagram shows a structural block diagram of an evaluation device for a wave model according to this application, the device comprising:

[0114] The first determining module 11 is used to determine multiple types of parameters in the general wave model;

[0115] The second determining module 12 is used to determine multiple candidate values ​​of the parameter of any type.

[0116] The first acquisition module 13 is used to acquire multiple parameter combinations, each parameter combination including a candidate value of a parameter of each type; at least one parameter of the same type in any two parameter combinations has different candidate values.

[0117] The setting module 14 is used to set the parameters of each type in the general wave model according to a candidate value of each type of parameter in the parameter combination for any parameter combination, so as to obtain the candidate wave model corresponding to the parameter combination; the second acquisition module 15 is used to acquire at least one type of wave index simulated by the candidate wave model corresponding to the parameter combination; the third acquisition module 16 is used to acquire at least one type of actual wave index of the target sea area; the fourth acquisition module 17 is used to acquire the error index of the candidate wave model corresponding to the parameter combination according to the at least one type of wave index simulated by the candidate wave model corresponding to the parameter combination and the at least one type of actual wave index of the target sea area.

[0118] The third determination module 18 is used to determine the candidate wave model with the lowest error index as the wave model suitable for the target sea area.

[0119] In one optional implementation, the second acquisition module includes:

[0120] The first effective wave height acquisition unit is used to acquire the effective wave height of the wave simulated by the candidate wave model corresponding to the parameter combination;

[0121] And / or,

[0122] The first maximum wave height acquisition unit is used to acquire the maximum wave height of the wave simulated by the candidate wave model corresponding to the parameter combination;

[0123] And / or,

[0124] The first spectral peak period acquisition unit is used to acquire the spectral peak period of the wave simulated by the candidate wave model corresponding to the parameter combination;

[0125] And / or,

[0126] The first average period acquisition unit is used to acquire the average period of the waves simulated by the candidate wave model corresponding to the parameter combination.

[0127] And / or,

[0128] The first zero-crossing period acquisition unit is used to acquire the zero-crossing period of the wave simulated by the candidate wave model corresponding to the parameter combination.

[0129] In one optional implementation, the third acquisition module includes:

[0130] The second significant wave height acquisition unit is used to acquire the actual significant wave height of the waves in the target sea area;

[0131] And / or,

[0132] The second maximum wave height acquisition unit is used to acquire the actual maximum wave height of the waves in the target sea area;

[0133] And / or,

[0134] The second peak period acquisition unit is used to acquire the actual wave peak period of the target sea area;

[0135] And / or,

[0136] The second average period acquisition unit is used to acquire the actual average period of the waves in the target sea area;

[0137] And / or,

[0138] The second zero-crossing period acquisition unit is used to acquire the actual zero-crossing period of the waves in the target sea area.

[0139] In one optional implementation, the fourth acquisition module includes:

[0140] The first error calculation unit is used to calculate the square of the difference between the effective wave height of the waves simulated by the candidate wave model corresponding to the parameter combination and the effective wave height of the actual waves in the target sea area, and use it as the error index of the candidate wave model corresponding to the parameter combination.

[0141] And / or,

[0142] The second error calculation unit is used to calculate the square of the difference between the maximum wave height simulated by the candidate wave model corresponding to the parameter combination and the maximum wave height of the actual waves in the target sea area, and use it as the error index of the candidate wave model corresponding to the parameter combination.

[0143] And / or,

[0144] The third error calculation unit is used to calculate the square of the difference between the peak period of the wave simulated by the candidate wave model corresponding to the parameter combination and the peak period of the actual wave in the target sea area, and use it as the error index of the candidate wave model corresponding to the parameter combination.

[0145] And / or,

[0146] The fourth error calculation unit is used to calculate the square of the difference between the average period of the waves simulated by the candidate wave model corresponding to the parameter combination and the average period of the actual waves in the target sea area, and use it as the error index of the candidate wave model corresponding to the parameter combination.

[0147] And / or,

[0148] The fifth error calculation unit is used to calculate the square of the difference between the zero-crossing period of the wave simulated by the candidate wave model corresponding to the parameter combination and the zero-crossing period of the actual wave in the target sea area, and use it as the error index of the candidate wave model corresponding to the parameter combination.

[0149] In one alternative implementation, the parameter of the type is the energy loss caused by bottom friction;

[0150] The second determining module includes:

[0151] The first determining unit is used to determine the water depth of the target sea area;

[0152] The first setting unit is used to set multiple values ​​of bottom friction resistance according to the water depth of the target sea area;

[0153] The first energy loss calculation unit is used to calculate the energy loss caused by the bottom friction resistance based on the set bottom friction resistance value.

[0154] The second setting unit is used to set the calculated energy loss caused by bottom friction as a candidate value for the parameter of the type.

[0155] In an optional implementation, the first setting unit includes:

[0156] The first setting subunit is used to set the bottom friction value to 0.02 when the water depth in the target sea area is less than the preset water depth.

[0157] or,

[0158] The second setting subunit is used to set the bottom friction value to 0.03 when the water depth in the target sea area is greater than or equal to the preset water depth.

[0159] In one alternative implementation, the parameter of the type is the energy loss caused by the nonlinear interaction between waves;

[0160] The second determining module includes:

[0161] The second determining unit is used to determine the wind cycle in the target sea area;

[0162] The third setting unit is used to set the coupling between wind and waves according to the wind cycle of the target sea area; the coupling includes coupling and non-coupling.

[0163] The second energy loss calculation unit is used to calculate the energy loss caused by the nonlinear interaction between waves based on the coupling between wind and waves.

[0164] The fourth setting unit is used to set the calculated energy loss caused by bottom friction as a candidate value for the parameter of the aforementioned type.

[0165] In an optional implementation, the fourth setting unit includes:

[0166] The third setting subunit is used to set the wind and waves to be decoupled when the wind period in the target sea area is less than the preset period.

[0167] or,

[0168] The fourth setting subunit is used to set the coupling between wind and waves when the wind period in the target sea area is greater than the preset period.

[0169] This application utilizes differentiated parameter settings on a general wave model to obtain multiple candidate wave models with varying parameter values. Each candidate model is then tested, and the model with the smallest error relative to the actual wave conditions in the target sea area is selected as the applicable wave model for that area. The candidate wave model with the smallest error closely simulates the actual wave conditions in the target sea area, and the candidate wave model corresponding to this parameter combination performs better for that area. Thus, this application provides a wave model that more closely resembles the actual wave conditions in the target sea area, facilitating subsequent wave simulation in that region.

[0170] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0171] Optionally, this application also provides an electronic device, including: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the various processes of the above method embodiments and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0172] This application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described method embodiments and achieves the same technical effects. To avoid repetition, it will not be described again here. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0173] Figure 3This is a block diagram illustrating an electronic device 800. For example, the electronic device 800 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc.

[0174] Reference Figure 3 The electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power supply component 806, a multimedia component 808, an audio component 810, an input / output (I / O) interface 812, a sensor component 814, and a communication component 816.

[0175] Processing component 802 typically controls the overall operation of electronic device 800, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 802 may include one or more modules to facilitate interaction between processing component 802 and other components. For example, processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.

[0176] Memory 804 is configured to store various types of data to support the operation of electronic device 800. Examples of such data include instructions for any application or method operating on electronic device 800, contact data, phonebook data, messages, images, videos, etc. Memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0177] Power supply component 806 provides power to various components of electronic device 800. Power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 800.

[0178] Multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 808 includes a front-facing camera and / or a rear-facing camera. When the electronic device 800 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0179] Audio component 810 is configured to output and / or input audio signals. For example, audio component 810 includes a microphone (MIC) configured to receive external audio signals when electronic device 800 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 804 or transmitted via communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

[0180] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0181] Sensor assembly 814 includes one or more sensors for providing state assessments of various aspects of electronic device 800. For example, sensor assembly 814 can detect the on / off state of electronic device 800, the relative positioning of components such as the display and keypad of electronic device 800, changes in position of electronic device 800 or a component of electronic device 800, the presence or absence of user contact with electronic device 800, orientation or acceleration / deceleration of electronic device 800, and temperature changes of electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 814 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0182] Communication component 816 is configured to facilitate wired or wireless communication between electronic device 800 and other devices. Electronic device 800 can access wireless networks based on communication standards, such as WiFi, carrier networks (such as 2G, 3G, 4G, or 5G), or combinations thereof. In one exemplary embodiment, communication component 816 receives broadcast signals or broadcast operation information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 816 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0183] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0184] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, which can be executed by a processor 820 of an electronic device 800 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0185] Figure 4 This is a block diagram of an electronic device 1900 shown in this application. For example, the electronic device 1900 can be provided as a server.

[0186] Reference Figure 4 The electronic device 1900 includes a processing component 1922, which further includes one or more processors, and memory resources represented by memory 1932 for storing instructions, such as application programs, that can be executed by the processing component 1922. The application programs stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1922 is configured to execute instructions to perform the methods described above.

[0187] Electronic device 1900 may also include a power supply component 1926 configured to perform power management of electronic device 1900, a wired or wireless network interface 1950 configured to connect electronic device 1900 to a network, and an input / output (I / O) interface 1958. Electronic device 1900 can operate on an operating system stored in memory 1932, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, or similar.

[0188] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0189] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0190] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0191] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application 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 implementation should not be considered beyond the scope of this application.

[0192] Those skilled in the art will 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.

[0193] In the embodiments provided in this application, 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 apparatuses or units may be electrical, mechanical, or other forms.

[0194] 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.

[0195] In addition, the functional units in the various embodiments of this application 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.

[0196] 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 application, in essence, 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 application. 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.

[0197] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method of assessing a wave model, characterized by, The method comprises: determining parameters of multiple categories in a general wave model; for any one category of parameters, determining multiple candidate values of the category of parameters; obtaining multiple parameter combinations, each parameter combination including one candidate value of each category of parameters; at least one candidate value of the same category of parameters in any two parameter combinations is different; for any one parameter combination, setting each category of parameters in the general wave model according to one candidate value of each category of parameters in the parameter combination to obtain a candidate wave model corresponding to the parameter combination; obtaining at least one category of wave indexes simulated by the candidate wave model corresponding to the parameter combination; obtaining actual at least one category of wave indexes of a target sea area; and obtaining an error index of the candidate wave model corresponding to the parameter combination according to at least one category of wave indexes simulated by the candidate wave model corresponding to the parameter combination and the actual at least one category of wave indexes of the target sea area; determining the candidate wave model with the lowest error index as the wave model suitable for the target sea area; the determination of the candidate wave model with the lowest error index as the wave model suitable for the target sea area comprises: sorting each candidate wave model in the order from low to high according to the error index of each candidate wave model, then selecting the candidate wave model ranked first and taking it as the wave model suitable for the target sea area; the obtaining of at least one category of wave indexes simulated by the candidate wave model corresponding to the parameter combination comprises: obtaining the significant wave height of the wave simulated by the candidate wave model corresponding to the parameter combination; and obtaining the maximum wave height of the wave simulated by the candidate wave model corresponding to the parameter combination; and obtaining the spectral peak period of the wave simulated by the candidate wave model corresponding to the parameter combination; and obtaining the average period of the wave simulated by the candidate wave model corresponding to the parameter combination; and obtaining the zero-crossing point period of the wave simulated by the candidate wave model corresponding to the parameter combination; the obtaining of the significant wave height of the wave simulated by the candidate wave model corresponding to the parameter combination comprises: obtaining the zero-order momentum of the wave simulated by the candidate wave model corresponding to the parameter combination, and calculating the significant wave height of the wave simulated by the candidate wave model corresponding to the parameter combination according to the zero-order momentum according to the following formula: wherein m0is the zeroth order momentum of the wave simulated by the candidate wave model corresponding to the parameter combination, H m0 is the significant wave height of the wave simulated by the candidate wave model corresponding to the parameter combination; The acquiring the maximum wave height of the wave simulated by the candidate wave model corresponding to the parameter combination comprises: calculating the maximum wave height H of the wave simulated by the candidate wave model corresponding to the parameter combination by the following manner max : wherein N is the number of waves, H m0 is the significant wave height of the wave simulated by the candidate wave model corresponding to the parameter combination; k is the wave number corresponding to the spectral peak wave period, and d is the water depth; the obtaining of the spectral peak period of the wave simulated by the candidate wave model corresponding to the parameter combination comprises: calculating the spectral peak period of the wave simulated by the candidate wave model corresponding to the parameter combination through the following formula: T p a spectral peak period of a wave simulated by the candidate wave model corresponding to the parameter combination; Spectrum peak frequency f p Calculated by using a parabolic fit between the individual peaks of the one-dimensional spectrum; The acquiring the average period of the wave simulated by the candidate wave model corresponding to the parameter combination comprises: calculating the average period T of the wave simulated by the candidate wave model corresponding to the parameter combination by the following formula 01 : m0 is the zero-order momentum of the wave simulated by the candidate wave model corresponding to the parameter combination, and m1 is the first-order momentum of the wave simulated by the candidate wave model corresponding to the parameter combination; The acquiring the zero-crossing point period of the wave simulated by the candidate wave model corresponding to the parameter combination comprises: calculating the zero-crossing point period T of the wave simulated by the candidate wave model corresponding to the parameter combination through the following formula 02 : m0 is the zero-order momentum of the wave simulated by the candidate wave model corresponding to the parameter combination, and m2 is the second-order momentum of the wave simulated by the candidate wave model corresponding to the parameter combination; the actual at least one category of wave indexes of the target sea area is obtained through satellite measured remote sensing data; the obtaining of the actual at least one category of wave indexes of the target sea area comprises: an actual significant wave height of the target sea area; and, an actual maximum wave height of the target sea area; and, an actual spectral peak period of the target sea area; and, an actual mean period of the target sea area; and, an actual zero-crossing period of the target sea area; the parameter of the type is energy loss caused by bottom friction; the determining of the multiple candidate values of the parameter of the type comprises: determining a water depth of the target sea area; setting multiple values of bottom friction according to the water depth of the target sea area; for any one of the set values of bottom friction, calculating the energy loss caused by bottom friction according to the value, to obtain the energy loss caused by bottom friction corresponding to the value; setting the energy loss caused by bottom friction corresponding to each value as a candidate value of the parameter of the type respectively; the setting of the values of bottom friction according to the water depth of the target sea area comprises: in the case that the water depth of the target sea area is less than a preset water depth, setting the value of bottom friction as 0.02; or, in the case that the water depth of the target sea area is greater than or equal to the preset water depth, setting the value of bottom friction as 0.03; the parameter of the type is energy loss caused by nonlinear interaction between waves; the determining of the multiple candidate values of the parameter of the type comprises: determining a period of wind of the target sea area; setting a coupling condition of wind and wave according to the period of wind of the target sea area; the coupling condition comprises coupling and non-coupling; calculating the energy loss caused by nonlinear interaction between waves according to the coupling condition of wind and wave; setting the calculated energy loss caused by bottom friction as a candidate value of the parameter of the type; the setting of the coupling condition of wind and wave according to the period of wind of the target sea area comprises: in the case that the period of wind of the target sea area is less than a preset period, setting that wind and wave are not coupled; or, in the case that the period of wind of the target sea area is greater than the preset period, setting that wind and wave are coupled.

2. The method of claim 1, wherein, the obtaining of the error index of the candidate wave model corresponding to the parameter combination according to at least one wave index of the target sea area and at least one wave index simulated by the candidate wave model corresponding to the parameter combination comprises: calculating the square of the difference between the significant wave height of the wave simulated by the candidate wave model corresponding to the parameter combination and the actual significant wave height of the target sea area, and taking the square as the error index of the candidate wave model corresponding to the parameter combination; and, calculating the square of the difference between the maximum wave height of the wave simulated by the candidate wave model corresponding to the parameter combination and the actual maximum wave height of the target sea area, and taking the square as the error index of the candidate wave model corresponding to the parameter combination; and, calculating the square of the difference between the spectral peak period of the wave simulated by the candidate wave model corresponding to the parameter combination and the actual spectral peak period of the target sea area, and taking the square as the error index of the candidate wave model corresponding to the parameter combination; and, square the difference between the average period of the wave simulated by the candidate wave model corresponding to the parameter combination and the average period of the actual wave of the target sea area, and take it as the error index of the candidate wave model corresponding to the parameter combination; and, square the difference between the zero-crossing point period of the wave simulated by the candidate wave model corresponding to the parameter combination and the zero-crossing point period of the actual wave of the target sea area, and take it as the error index of the candidate wave model corresponding to the parameter combination.

3. An apparatus for evaluating a wave model, characterized by The device comprises: a first determination module configured to determine a plurality of categories of parameters in a general wave model; a second determination module configured to, for any one category of parameters, determine a plurality of candidate values of the category of parameters; a first acquisition module configured to acquire a plurality of parameter combinations, each parameter combination comprising one candidate value of each category of parameters; at least one candidate value of the same category of parameters in any two parameter combinations being different; a setting module configured to, for any one parameter combination, set each category of parameters in the general wave model according to one candidate value of each category of parameters in the parameter combination, to obtain a candidate wave model corresponding to the parameter combination; a second acquisition module configured to acquire at least one category of wave indexes simulated by the candidate wave model corresponding to the parameter combination; a third acquisition module configured to acquire actual at least one category of wave indexes of the target sea area; and a fourth acquisition module configured to acquire an error index of the candidate wave model corresponding to the parameter combination according to the at least one category of wave indexes simulated by the candidate wave model corresponding to the parameter combination and the actual at least one category of wave indexes of the target sea area; a third determination module configured to determine the candidate wave model with the lowest error index as the wave model applicable to the target sea area; the third determination module is specifically configured to sort each candidate wave model in the order from low to high according to the respective error indexes, and then select the candidate wave model ranked first, and take it as the wave model applicable to the target sea area; the second acquisition module comprises: a first significant wave height acquisition unit configured to acquire the significant wave height of the wave simulated by the candidate wave model corresponding to the parameter combination; and, a first maximum wave height acquisition unit configured to acquire the maximum wave height of the wave simulated by the candidate wave model corresponding to the parameter combination; and, a first spectral peak period acquisition unit configured to acquire the spectral peak period of the wave simulated by the candidate wave model corresponding to the parameter combination; and, a first average period acquisition unit configured to acquire the average period of the wave simulated by the candidate wave model corresponding to the parameter combination; and, a first zero-crossing point period acquisition unit configured to acquire the zero-crossing point period of the wave simulated by the candidate wave model corresponding to the parameter combination; the first significant wave height acquisition unit is specifically configured to: acquire the zeroth order momentum of the wave simulated by the candidate wave model corresponding to the parameter combination, and calculate the significant wave height of the wave simulated by the candidate wave model corresponding to the parameter combination according to the zeroth order momentum according to the following formula: wherein m0is the zeroth order momentum of the wave simulated by the candidate wave model corresponding to the parameter combination, H m0 is the significant wave height of the wave simulated by the candidate wave model corresponding to the parameter combination. The first maximum wave height acquisition unit is specifically configured to calculate the maximum wave height H of the wave simulated by the candidate wave model corresponding to the parameter combination by the following manner max : wherein N is the number of waves, H m0 is the significant wave height of the wave simulated by the candidate wave model corresponding to the parameter combination; k is the wave number corresponding to the spectral peak wave period, and d is the water depth; The first spectral peak period acquisition unit is specifically configured to calculate the spectral peak period of the wave simulated by the candidate wave model corresponding to the parameter combination according to the following formula: T p a spectral peak period of the waves simulated by the candidate wave model corresponding to the parameter combination; Spectrum peak frequency f p Calculated by using a parabolic fit between the individual peaks of the one-dimensional spectrum; The first average period acquisition unit is specifically configured to calculate the average period T of the wave simulated by the candidate wave model corresponding to the parameter combination by the following formula 01 : m0 is the zero-order momentum of the wave simulated by the candidate wave model corresponding to the parameter combination, and m1 is the first-order momentum of the wave simulated by the candidate wave model corresponding to the parameter combination; The first zero-crossing point acquisition unit is specifically configured to calculate the zero-crossing point T of the wave simulated by the candidate wave model corresponding to the parameter combination according to the following formula 02 : m0 is the zero-order momentum of the wave simulated by the candidate wave model corresponding to the parameter combination, and m2 is the second-order momentum of the wave simulated by the candidate wave model corresponding to the parameter combination; The actual at least one kind of wave index of the target sea area is obtained through satellite measured remote sensing data; The third acquisition module comprises: The second significant wave height acquisition unit is configured to acquire the actual significant wave height of the wave of the target sea area; and, The second maximum wave height acquisition unit is configured to acquire the actual maximum wave height of the wave of the target sea area; and, The second spectral peak period acquisition unit is configured to acquire the actual spectral peak period of the wave of the target sea area; and, The second average period acquisition unit is configured to acquire the actual average period of the wave of the target sea area; and, The second zero-crossing point period acquisition unit is configured to acquire the actual zero-crossing point period of the wave of the target sea area; The kind of parameter is energy loss caused by bottom friction; The second determination module comprises: The first determination unit is configured to determine the water depth of the target sea area; The first setting unit is configured to set a plurality of values of the bottom friction according to the water depth of the target sea area; The first energy loss calculation unit is configured to calculate the energy loss caused by the bottom friction according to the set value of the bottom friction; The second setting unit is configured to set the calculated energy loss caused by the bottom friction as a candidate value of the kind of parameter; The first setting unit comprises: The first setting sub-unit is configured to set the value of the bottom friction as 0.02 when the water depth of the target sea area is less than a preset water depth; or, The second setting sub-unit is configured to set the value of the bottom friction as 0.03 when the water depth of the target sea area is greater than or equal to the preset water depth; The kind of parameter is energy loss caused by nonlinear interaction between waves; The second determination module comprises: The second determination unit is configured to determine the period of the wind of the target sea area; The third setting unit is configured to set the coupling condition between the wind and the wave according to the period of the wind of the target sea area; the coupling condition comprises coupling and non-coupling; The second energy loss calculation unit is configured to calculate the energy loss caused by the nonlinear interaction between the waves according to the coupling condition between the wind and the wave; The fourth setting unit is configured to set the calculated energy loss caused by the bottom friction as a candidate value of the kind of parameter; The fourth setting unit comprises: The third setting sub-unit is configured to set that the wind and the wave are not coupled when the period of the wind of the target sea area is less than a preset period; or, The fourth setting sub-unit is configured to set that the wind and the wave are coupled when the period of the wind of the target sea area is greater than the preset period.

4. The apparatus of claim 3, wherein, The fourth acquisition module comprises: a first error calculation unit configured to calculate a square of a difference between a significant wave height of the wave simulated by the candidate wave model corresponding to the parameter combination and a significant wave height of the actual wave in the target sea area, and use the square as an error indicator of the candidate wave model corresponding to the parameter combination; and, a second error calculation unit configured to calculate a square of a difference between a maximum wave height of the wave simulated by the candidate wave model corresponding to the parameter combination and a maximum wave height of the actual wave in the target sea area, and use the square as an error indicator of the candidate wave model corresponding to the parameter combination; and, a third error calculation unit configured to calculate a square of a difference between a spectral peak period of the wave simulated by the candidate wave model corresponding to the parameter combination and a spectral peak period of the actual wave in the target sea area, and use the square as an error indicator of the candidate wave model corresponding to the parameter combination; and, a fourth error calculation unit configured to calculate a square of a difference between a mean period of the wave simulated by the candidate wave model corresponding to the parameter combination and a mean period of the actual wave in the target sea area, and use the square as an error indicator of the candidate wave model corresponding to the parameter combination; and, a fifth error calculation unit configured to calculate a square of a difference between a zero-crossing period of the wave simulated by the candidate wave model corresponding to the parameter combination and a zero-crossing period of the actual wave in the target sea area, and use the square as an error indicator of the candidate wave model corresponding to the parameter combination.

5. An electronic device, comprising: comprising: a processor, a memory, and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the method according to any one of claims 1 to 2.

6. A computer readable storage medium characterized in that, a computer readable storage medium storing a computer program, the computer program, when executed by a processor, implementing the method according to any one of claims 1 to 2.

Images