A typhoon prediction and water power numerical simulation-based fishery port and fishing boat berth dynamic optimization method and system

Abstract

This invention discloses a method and system for dynamic optimization of fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation. The method includes the following steps: Step 1: Collect target fishing port data and fishing vessel information to establish a basic spatial database for the fishing port; Step 2: Obtain data from meteorological data sources; Step 3: Combine standard wind field data with a parameterized wind field model to generate a fused wind field; Step 4: Construct a grid file and a corresponding mapping table; Step 5: Obtain the open sea wave-tide coupling field for the entire typhoon process based on a preset coupling time step; Step 6: Simulate waves to generate a wave height distribution map; Step 7: Divide the area into berthing zones with different safety levels; Step 8: Dynamically divide the berthing zones according to the specific situation of fishing vessels returning to port before the typhoon. This invention dynamically optimizes fishing vessel berths in fishing ports through typhoon forecasting and refined wave simulation. By dynamically delineating safe berthing waters based on the berthing wave height standards for different vessel types, it can effectively optimize the berthing of fishing vessels in fishing ports.

Description

Technical Field

[0001] This invention relates to the fields of marine engineering, port management, and disaster prevention and mitigation, and in particular to a method and system for dynamic optimization of fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation. Background Technology

[0002] Coastal fishing ports, as core shelters for fishing vessels, bear the dual responsibility of ensuring fishery production and protecting the lives and property of communities. Against the backdrop of global climate change, the extreme intensity of typhoons in the Northwest Pacific is on the rise, and the frequent occurrence of super typhoons poses a complex threat to port structures and anchored vessels due to the combined effects of storm surges and extreme waves. Currently available technologies related to port disaster prevention and control are mostly found in commercial port typhoon emergency response systems, AIS-based vessel traffic management systems, and simple electronic fencing for anchorages. A few solutions involving hydrodynamic simulation cannot be adapted online for the specific path of each typhoon. Furthermore, while the application of shallow-water wave models in nearshore port engineering is documented in academic literature, a standardized, patented implementation plan for emergency command in fishing ports has not yet been developed.

[0003] While most existing fishing ports have berth numbers and anchorage zones for routine management, in typhoon emergency scenarios, the mooring positions of fishing vessels entering the port area are mainly determined by port officials based on experience or by fishermen finding relatively leeward positions themselves. There is a lack of quantitative assessment of the spatial distribution of wave height within the port under different typhoon paths and intensities. This leads to hidden risk blind spots within so-called safe zones—diffraction waves near the entrance, secondary reflection waves behind breakwaters, and wave height increases in shallow water areas due to shallowing can all create localized high-risk areas under specific wind directions. Early disaster prevention assessments often used the static historical highest tide level + design wave height method, using fixed values ​​to delineate inundation lines and mooring loads. However, the spatial distribution of wave height in a single super typhoon exhibits strong non-stationarity and time-varying asymmetry—the maximum wave height does not simply correspond to a fixed quadrant but changes with the typhoon structure. Relying solely on empirical wind field or low-resolution global reanalysis data to drive wave models often underestimates extreme wave conditions near the shore, especially within the port. Traditional spectral wave models perform well over large sea areas, but they are essentially statistical descriptions of wave energy density and tend to output smooth wave height fields in space. They are difficult to characterize the local diffraction shadows, wave focusing areas, and near-field secondary wave fields formed by breakwater transmission caused by the complex boundaries of the port area. Therefore, this invention proposes a dynamic optimization method and system for fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation to solve the problems existing in the prior art. Summary of the Invention

[0004] To address the aforementioned problems, the present invention aims to propose a dynamic optimization method and system for fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation. This method and system dynamically optimizes fishing vessel berths in fishing ports through typhoon forecasting and refined wave simulation, solving the problem that relying solely on empirical wind field data or low-resolution global reanalysis data to drive wave models underestimates the resistance to extreme waves near the shore and within the port. By dynamically delineating safe berthing areas according to the berthing wave height standards for different vessel types, safe berthing areas can be defined. While ensuring the safety of fishing vessels, it maximizes the use of sheltered waters within the port, solving the problem that the berthing positions of fishing vessels entering the port area are mainly determined by port authorities based on experience or fishermen finding relatively leeward positions themselves, lacking quantitative assessment of the spatial distribution of wave height within the port under different typhoon paths / intensities.

[0005] To achieve the objectives of this invention, the invention is implemented through the following technical solution: a method and system for dynamic optimization of fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation, comprising the following steps: Step 1: Construction of the basic spatial database of fishing ports. Collect data on the topography, underwater elevation, shoreline and breakwater structure of the target fishing port, as well as data on berths and anchorages in the port area. At the same time, collect information on the size and draft of registered fishing vessels to establish the basic spatial database of fishing ports. Step 2: Typhoon forecast access and analysis, obtaining time-series data on the center position, air pressure, wind speed, and movement speed of the target typhoon from meteorological data sources; Step 3: Wind field fusion and reconstruction. Combining large-scale standard wind field data with a parameterized wind field model specifically designed for typhoon structures, a more accurate fused wind field covering the computational area is generated. Step 4: Construct a multi-level nested unstructured mesh. Establish a three-level computational subdomain centered on the target fishing port. Use unstructured triangular meshes to subdivide the offshore area subdomain, nearshore transition subdomain, and port fine subdomain respectively. Output the mesh file and the corresponding mapping table. Step 5: Wave-storm surge bidirectional coupling simulation. Iterative data exchange is performed based on a preset coupling time step to provide real-time water level and flow velocity fields, and to obtain the outer sea wave-tide coupling field for the entire typhoon process. Step 6: Refined simulation of shallow water waves in the harbor. Extract the wave spectrum parameters from Step 5 as boundary conditions, input the wave model for the shallow water area, and simulate the deformation, diffraction, reflection and breaking processes of waves after entering the harbor area to obtain a detailed wave height distribution map inside the harbor area. Step 7: Safe berthing area division. Based on the size and seakeeping capability of the fishing boats, set different levels of critical wave height thresholds and compare them with the wave height distribution map generated in Step 6 to divide the port area into berthing areas with different safety levels. Step 8: Dynamic berth optimization. Based on the specific situation of fishing vessels returning to port before the typhoon, and in conjunction with the aforementioned safe berth areas, water depth conditions, and vessel spacing requirements, the berthing areas are dynamically divided.

[0006] A further improvement is that the time-series dataset of key typhoon parameters formed from the typhoon forecast data in step two is as follows: τ = {t i , λ i , φ i , p c,i V max,i V f,i} i=1…N Where τ is the time series dataset of key typhoon parameters, {t i , λ i , φ i} represents the latitude and longitude sequence of the typhoon center, p c,i V is the central air pressure. max,i For the maximum sustained wind speed, V f,i This refers to movement speed.

[0007] A further improvement is made in the following: the formula for the fused wind field model in step three is: , in, V To integrate the wind field, VERA5 The wind speed at 10 meters per second for ERA5. λ These are the weighting coefficients. r Distance from the center of the typhoon Rmax The radius of maximum wind speed. n The constant parameter is set to 9.

[0008] A further improvement is made in the following: the expression for the tangential wind speed of the fused wind field in step three is: in, r This refers to the distance from the center of the typhoon. P amd For ambient air pressure, P c The central air pressure, ρ air density, f Coriolis parameters, B For shape parameters, R max The radius is the radius of maximum wind speed.

[0009] The further improvement is that: in step four, the grid density transition ratio is 1.3:1, the side length of the coarsest grid in the offshore sub-domain is 800-2000m, the side length of the transition grid in the nearshore transition sub-domain is 100-300m, and the side length of the fine grid in the port fine sub-domain is 5-15m.

[0010] A dynamic optimization system for fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation is characterized by comprising a data layer, an analysis layer, and an implementation layer. The data layer is used to connect and receive data, and to provide a data foundation using big data and weather forecast information. The analysis layer is used to analyze weather and geographical data to forecast tidal and sea conditions and to simulate waves from the open sea to the nearshore. The implementation layer is used to adjust the safety zoning level within the berth area in real time based on wave data.

[0011] Further improvements are made in that: the data layer includes a basic data management module and a meteorological access module. The basic data management module is used to store and manage the topography, underwater elevation, shoreline and breakwater structure data of the target fishing port, as well as the berth index table. The meteorological access module is used to connect to the meteorological business interface to periodically obtain typhoon forecast information.

[0012] Further improvements are made in the following aspects: The analysis layer includes a hydrodynamic module, a wave module, and a coupling module. The hydrodynamic module is used to accurately predict tides by using the astronomical tidal harmonic constant and integrating meteorological tidal data from long-term tide gauge stations. The wave module is used to provide wave output spectra to achieve accurate wave transmission from the open sea to the nearshore. The coupling module is used to realize the coupled simulation of waves and hydrodynamics through a two-way dynamic coupling framework, and iterative data exchange is performed between the hydrodynamic module and the wave module based on a preset coupling time step.

[0013] Further improvements are made in that: the implementation layer includes a wave height safety zoning module and a berth optimization module. The wave height safety zoning module is used to read wave module data to simulate the deformation, diffraction, reflection and breaking process of waves after entering the port area, and output a graded berth vector map. The berth optimization module is used to input the list of returning vessels and safety zoning, and output the target berth coordinates for each vessel.

[0014] The beneficial effects of this invention are as follows: This invention dynamically optimizes fishing vessel berths in fishing ports through typhoon forecasting and refined wave simulation, solving the problem that relying solely on empirical wind field data or low-resolution global reanalysis data to drive wave models underestimates the resistance to extreme waves near the shore and within the port. By dynamically delineating safe berthing areas based on the berthing wave height standards for different vessel types, this invention maximizes the utilization of sheltered waters within the port while ensuring the safety of fishing vessels. It also addresses the issue that berthing positions for fishing vessels entering the port area are mainly determined by port officials based on experience or fishermen finding relatively leeward positions themselves, lacking a quantitative assessment of the spatial distribution of wave height within the port under different typhoon paths / intensities. Attached Figure Description

[0015] Figure 1 This is a flowchart of the steps of the present invention; Figure 2 This is a system architecture diagram of the present invention. Detailed Implementation

[0016] To enhance understanding of the present invention, the present invention will be further described in detail below with reference to embodiments. These embodiments are only used to explain the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0017] according to Figure 1 , Figure 2 As shown, this embodiment provides a method and system for dynamic optimization of fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation, including the following steps: Step 1: Construction of the Port Spatial Basic Database. This step involves collecting data on the topography, underwater elevation, shoreline and breakwater structure of the target port, as well as berth and anchorage data. Simultaneously, it collects information on the size and draft of registered fishing vessels to establish the port spatial basic database. This creates a precise digital twin of the port, avoiding omissions and errors from manual statistics. It provides a reliable geographical and vessel foundation for subsequent wave simulation, safety zoning, and berth scheduling, ensuring the accuracy of the entire solution from the outset. Standardization of fishing vessel parameters supports differentiated safety assessments, avoiding the traditional "one-size-fits-all" berth allocation method. Step 2: Typhoon forecast access and analysis. Obtain time-series data on the center position, air pressure, wind speed, and movement speed of the target typhoon from meteorological data sources. By obtaining the typhoon's path and intensity in advance, we can ensure forward-looking decision-making. The time series dataset of key typhoon parameters formed from typhoon forecast data is as follows: τ = {t i , λ i , φ i , p c,i V max,i V f,i} i=1…N Where τ is the time series dataset of key typhoon parameters, {t i , λ i , φ i} represents the latitude and longitude sequence of the typhoon center, p c,i V is the central air pressure. max,i For the maximum sustained wind speed, V f,i This refers to movement speed.

[0018] Step 3: Wind Field Fusion and Reconstruction. Combining large-scale standard wind field data with a parameterized wind field model specifically designed for typhoon structures, a more accurate fused wind field covering the computational area is generated. ERA5's 10-meter wind field has a time resolution of 1 hour and a spatial resolution of 0.25°×0.25°, serving as a large-scale background field. The parameterized typhoon model utilizes the typhoon's central pressure, maximum sustained wind speed, and maximum wind speed radius to invert the axisymmetric tangential wind speed. The tangential wind speed near the typhoon center is based on the fused wind field, while the wind speed in the outer periphery of the typhoon is based on the 10-meter wind field of ERA5. This addresses the deficiency of insufficient accuracy of ERA5 wind field in the typhoon core area. The fused wind field is closer to the actual measurement, providing a reliable wind field foundation for subsequent numerical simulations of tides and waves.

[0019] The formula for the fused wind field model is: , in, V To integrate the wind field, VERA5 The wind speed at 10 meters per second for ERA5. λ These are the weighting coefficients. r Distance from the center of the typhoon Rmax The radius of maximum wind speed. n The constant parameter is set to 9.

[0020] The expression for the tangential wind speed of the merged wind field is: in, r This refers to the distance from the center of the typhoon. P amd For ambient air pressure, P c The central air pressure, ρ air density, f Coriolis parameters, B For shape parameters, R max The radius is the radius of maximum wind speed.

[0021] Step 4: Construct a multi-level nested unstructured mesh. A three-level computational subdomain is established centered on the target fishing port. An unstructured triangular mesh is used to subdivide the area into an offshore subdomain, a nearshore transition subdomain, and a fine-grained subdomain within the port. The mesh file and corresponding mapping table are output. The offshore subdomain covers a large sea area, simulating large-scale tidal waves and wind-generated waves. The nearshore transition subdomain covers the area surrounding the fishing port, bridging the open sea and port waves. The fine-grained subdomain within the port covers the harbor basin, channels, and wharf front area, focusing on local wave details. The mesh density transition ratio is 1.3:1. The coarsest mesh edge length in the offshore subdomain is 1000m, the transition edge length in the nearshore transition subdomain is 200m, and the fine mesh edge length in the fine-grained subdomain within the port is 10m. By using unstructured triangular meshes with fewer computational units, we can achieve more flexible and efficient high-resolution simulations in complex boundaries and key areas. We can also use a multi-level nesting strategy to meet the computational needs of both large-scale sea areas and small-scale port areas. We can reduce the amount of computation by using coarse meshes in the open sea and fine meshes in the port to capture local wave extremes.

[0022] Step 5: Wave-storm surge bidirectional coupling simulation. Iterative data exchange is performed based on a preset coupling time step to provide real-time water level and velocity fields, and to obtain the offshore wave-tide coupling field for the entire typhoon process. The hydrodynamic module provides water level and velocity to the wave module to correct the water depth and flow field environment for wave propagation. The bidirectional coupling considers the interaction between waves and tides, providing reliable offshore boundary conditions for subsequent shallow water wave simulation in the harbor.

[0023] Step Six: Refined simulation of shallow water waves within the harbor. Extract the wave spectrum parameters from Step Five as boundary conditions, input the wave model for the shallow water area, and simulate the deformation, diffraction, reflection, and breaking processes of waves after entering the harbor area to obtain a detailed wave height distribution map within the harbor area. This accurately reflects the wave deformation within the harbor, avoids underestimating the actual wave height, and provides key and detailed wave height data for the delineation of safe berth areas.

[0024] Step 7: Delineation of safe berthing areas. Based on the size and wave-keeping capability of fishing vessels, different levels of critical wave height thresholds are set and compared with the wave height distribution map generated in Step 6 to divide the port area into berthing areas of different safety levels. By dynamically delineating safe berthing waters according to the berthing wave height standards of different vessel types, the traditional "one-size-fits-all" allocation is effectively avoided.

[0025] Step 8: Dynamic Berth Optimization. Based on the specific situation of fishing vessels returning to port before the typhoon, and considering factors such as safe berth areas, water depth conditions, and vessel spacing requirements, berthing areas are dynamically divided. This dynamically adapts to the specific conditions of different typhoons, avoiding the limitations of fixed berth layouts, maximizing the number of vessels that can safely berth, and making full use of the sheltered waters within the harbor. It minimizes penalties in high-risk areas, reduces collision risks, and lowers the probability of accidents.

[0026] A dynamic optimization system for fishing vessel berths in fishing ports, based on typhoon forecasting and hydrodynamic numerical simulation, comprises a data layer, an analysis layer, and an implementation layer. The data layer connects to and receives data, utilizing big data and weather forecast information to provide a data foundation. This layer includes a basic data management module and a meteorological access module. The basic data management module stores and manages data on the target fishing port's topography, underwater elevation, shoreline and breakwater structure, as well as berth index tables. This provides a precise geographical and vessel basis for subsequent wave simulation, safety zoning, and berth scheduling, avoiding omissions and errors from manual statistics and ensuring the accuracy of the entire system from the outset. It also supports differentiated safety assessments through standardized fishing vessel parameters, moving away from the traditional "one-size-fits-all" berth allocation method. The meteorological access module connects to the meteorological service interface to periodically obtain typhoon forecast information. It periodically retrieves forecast data such as the center position, air pressure, wind speed, and movement speed of the target typhoon, parsing it into a structured time-series dataset containing information such as time, latitude, longitude, and intensity. This allows for advance acquisition of typhoon dynamics, ensuring forward-looking decision-making.

[0027] The analysis layer is used to analyze weather and geographic data to forecast tides and sea conditions, and to simulate waves from the open sea to the nearshore. The analysis layer includes a hydrodynamic module, a wave module, and a coupling module. The hydrodynamic module uses astronomical tidal harmonic constants and integrates meteorological tidal data from long-term tide gauge stations to accurately forecast tides, providing the wave module with real-time water level and current velocity data to help correct for wave propagation depth and current field environment. The wave module provides wave output spectra, enabling accurate wave propagation from the open sea to the nearshore. Driven by wind field integration, and combined with real-time water level and current velocity output from the hydrodynamic module, it simulates the generation and propagation process of open sea waves and outputs wave spectrum parameters. The coupling module uses a two-way dynamic coupling framework to achieve coupled simulation of waves and hydrodynamics. Based on a preset coupling time step, it iterative data exchange occurs between the hydrodynamic and wave modules to obtain the open sea wave-tidal coupling field for the entire typhoon process, providing reliable open sea boundary conditions for shallow water wave simulation within the harbor.

[0028] The implementation layer is used to adjust the safety zoning levels within the berth area in real time based on wave data. The implementation layer includes a wave height safety zoning module and a berth optimization module. The wave height safety zoning module reads wave data to simulate the deformation, diffraction, reflection, and breaking processes that occur after waves enter the port area, outputting a graded berth vector map. It dynamically delineates safe berths based on ship type differences, ensuring that each ship can find a matching berth. The berth optimization module takes the list of returning vessels and safety zoning as input and outputs the target berth coordinates for each ship. It dynamically adapts to the specific conditions of different typhoons, avoiding the limitations of fixed berth layouts, maximizing the use of the harbor's sheltered waters while ensuring safety, and reducing the risk of ship collisions and the probability of accidents.

[0029] The proposed method and system for dynamic optimization of fishing vessel berths in fishing ports, based on typhoon forecasting and hydrodynamic numerical simulation, first constructs a spatial database containing parameters of the fishing port topography, shoreline, berths, and fishing vessels, and integrates typhoon path, wind speed, and air pressure forecasts from the meteorological department. Next, it integrates a large-scale standard wind field with a parameterized typhoon model to generate a high-precision driving wind field, and establishes a three-level unstructured grid with progressively higher density from the open sea to the port. Then, through bidirectional coupling and iteration of the tidal-hydrodynamic model and the wave spectrum model, it simulates the open sea wave-tidal coupling field throughout the typhoon process, and uses this as a boundary to drive the shallow water wave model within the port, generating a wave height distribution map of the port area. Finally, it sets differentiated safe wave height thresholds based on the size of the fishing vessels, dynamically classifies the port area's safety level, and optimizes berthing scheduling based on the size, draft, and spacing requirements of returning fishing vessels, achieving a scientific closed loop from typhoon forecasting to typhoon avoidance decision-making.

[0030] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A dynamic optimization method for fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation, comprising the following steps: Step 1: Construction of the basic spatial database of fishing ports. Collect data on the topography, underwater elevation, shoreline and breakwater structure of the target fishing port, as well as data on berths and anchorages in the port area. At the same time, collect information on the size and draft of registered fishing vessels to establish the basic spatial database of fishing ports. Step 2: Typhoon forecast access and analysis, obtaining time-series data on the center position, air pressure, wind speed, and movement speed of the target typhoon from meteorological data sources; Step 3: Wind field fusion and reconstruction. Combining large-scale standard wind field data with a parameterized wind field model specifically designed for typhoon structures, a more accurate fused wind field covering the computational area is generated. Step 4: Construct a multi-level nested unstructured mesh. Establish a three-level computational subdomain centered on the target fishing port. Use unstructured triangular meshes to subdivide the offshore area subdomain, nearshore transition subdomain, and port fine subdomain respectively. Output the mesh file and the corresponding mapping table. Step 5: Wave-storm surge bidirectional coupling simulation. Iterative data exchange is performed based on a preset coupling time step to provide real-time water level and flow velocity fields, and to obtain the outer sea wave-tide coupling field for the entire typhoon process. Step 6: Refined simulation of shallow water waves in the harbor. Extract the wave spectrum parameters from Step 5 as boundary conditions, input the wave model for the shallow water area, and simulate the deformation, diffraction, reflection and breaking processes of waves after entering the harbor area to obtain a detailed wave height distribution map inside the harbor area. Step 7: Safe berthing area division. Based on the size and seakeeping capability of the fishing boats, set different levels of critical wave height thresholds and compare them with the wave height distribution map generated in Step 6 to divide the port area into berthing areas with different safety levels. Step 8: Dynamic berth optimization. Based on the specific situation of fishing vessels returning to port before the typhoon, and in conjunction with the aforementioned safe berth areas, water depth conditions, and vessel spacing requirements, the berthing areas are dynamically divided.

2. The method for dynamic optimization of fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation as described in claim 1, characterized in that: The typhoon key parameter time series dataset formed from the typhoon forecast data in step two is as follows: τ = {t i , l i , f i , p c,i , V max,i , V f,i } i=1…N Where τ is the time series dataset of key typhoon parameters, {t i , λ i , φ i } represents the latitude and longitude sequence of the typhoon center, p c,i V is the central air pressure. max,i For the maximum sustained wind speed, V f,i This refers to movement speed.

3. The method for dynamic optimization of fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation as described in claim 1, characterized in that: The formula for the fused wind field model in step three is: ， in, V To integrate the wind field, VERA5 This refers to the 10-meter wind speed of ERA5. λ These are the weighting coefficients. r Distance from the center of the typhoon Rmax The radius of maximum wind speed. n The constant parameter is set to 9.

4. The method for dynamic optimization of fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation as described in claim 1, characterized in that: The expression for the tangential wind speed of the merged wind field in step three is as follows: in, r This refers to the distance from the center of the typhoon. P amd For ambient air pressure, P c The central air pressure, ρ air density, f Coriolis parameters, B For shape parameters, R max The radius is the radius of maximum wind speed.

5. The method for dynamic optimization of fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation as described in claim 1, characterized in that: In step four, the grid density transition ratio is 1.3:1, the coarsest grid side length in the offshore sub-domain is 800-2000m, the transition side length in the nearshore transition sub-domain is 100-300m, and the fine grid side length in the port fine sub-domain is 5-15m.

6. A dynamic optimization system for fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation, as described in any one of claims 1-5, characterized in that: It includes a data layer, an analysis layer, and an implementation layer. The data layer is used to connect and receive data, and to provide a data foundation using big data and weather forecast information. The analysis layer is used to analyze weather and geographic data to forecast tides and sea conditions, and to simulate waves from the open sea to the nearshore. The implementation layer is used to adjust the safety zoning level in the berthing area in real time based on wave data.

7. The dynamic optimization system for fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation as described in claim 6, characterized in that: The data layer includes a basic data management module and a meteorological access module. The basic data management module is used to store and manage the topography, underwater elevation, shoreline and breakwater structure data of the target fishing port, as well as the berth index table. The meteorological access module is used to connect to the meteorological business interface to periodically obtain typhoon forecast information.

8. A dynamic optimization system for fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation as described in claim 6, characterized in that: The analysis layer includes a hydrodynamic module, a wave module, and a coupling module. The hydrodynamic module is used to accurately predict tides by using the astronomical tidal harmonic constant and integrating meteorological tidal data from long-term tide gauge stations. The wave module is used to provide wave output spectra to achieve accurate wave transmission from the open sea to the nearshore. The coupling module is used to realize the coupled simulation of waves and hydrodynamics through a two-way dynamic coupling framework, and iteratively exchange data between the hydrodynamic module and the wave module based on a preset coupling time step.

9. A dynamic optimization system for fishing vessel berths in fishing ports based on typhoon forecasting and hydrodynamic numerical simulation as described in claim 6, characterized in that: The implementation layer includes a wave height safety zoning module and a berth optimization module. The wave height safety zoning module is used to read wave module data to simulate the deformation, diffraction, reflection and breaking processes that occur after waves enter the port area, and output a tiered berth vector map. The berth optimization module is used to input the list of returning vessels and safety zoning, and output the target berth coordinates for each vessel.

Images