A Decision-Making Method and System for Ship Oil Spill Emergency Response Based on Multi-Source Data Fusion

Abstract

This invention relates to a method and system for decision-making in ship oil spill emergency response based on multi-source data fusion. The method includes: collecting multi-source data related to ship oil spill emergency response decision-making and preprocessing the multi-source data to obtain preprocessed multi-source data; calculating the environmental risk index of the sea area where the ship oil spill occurred based on the preprocessed multi-source data; assessing the emergency resource allocation capability based on the environmental risk index to obtain a resource response capability index; constructing a multi-objective route optimization model based on the environmental risk index and the resource response capability index to obtain a comprehensive decision index; performing dynamic path planning based on the environmental risk index, the resource response capability index, and the comprehensive decision index to obtain path optimization coefficients; calculating the final decision index based on the environmental risk index, the resource response capability index, the comprehensive decision index, and the path optimization coefficients, and executing the emergency response decision. This invention can improve the accuracy and efficiency of ship oil spill emergency response decision-making.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a decision-making method, system, electronic device, and non-transitory computer-readable storage medium for emergency response to ship oil spills based on multi-source data fusion. Background Technology

[0002] With the development of economic globalization, the scale of maritime transport continues to expand, and transportation safety issues are becoming increasingly prominent, especially the rising incidence of oil spills. After an oil spill, cleanup materials are usually stored at coastal docks or designated warehouses. Once an accident occurs, relevant emergency departments will quickly allocate cleanup materials to the accident area via land or sea transport, based on the specific location of the accident. Existing emergency response measures typically rely on pre-planned emergency material allocation routes and transport materials through manual operation or simple dispatch systems. Route selection mainly considers distance and time, basically using pre-set waterways and conventional traffic information, striving to complete the material transfer in the shortest possible time.

[0003] However, because oil spills typically occur in vast and unpredictable sea areas, the location of the spill is often difficult to predict, and oil spills may occur simultaneously in multiple locations, making it difficult to meet the requirements for the timeliness and adequacy of resource allocation. Furthermore, traditional methods rely on a single data source, such as route information and transport time, failing to fully consider various complex factors such as real-time sea conditions, weather changes, and maritime traffic flow. This can lead to suboptimal route selection in practice, delaying the efficiency of emergency response. Summary of the Invention

[0004] This invention addresses the technical problems existing in the prior art by providing a method, system, electronic device, and non-transitory computer-readable storage medium for ship oil spill emergency response decision-making based on multi-source data fusion, which can improve the accuracy and efficiency of ship oil spill emergency response decision-making.

[0005] The technical solution of the present invention to solve the above-mentioned technical problems is as follows:

[0006] This invention provides a decision-making method for emergency response to ship oil spills based on multi-source data fusion, the method comprising:

[0007] Collect multi-source data related to ship oil spill emergency response decision-making, and preprocess the multi-source data to obtain preprocessed multi-source data; the multi-source data includes real-time sea state data, meteorological data, maritime traffic data, and emergency resource data;

[0008] Based on the preprocessed multi-source data, the environmental risk index of the sea area where the oil spill occurred is calculated.

[0009] Based on the aforementioned environmental risk index, the emergency resource allocation capability is assessed to obtain the resource response capability index.

[0010] Based on the environmental risk index and the resource response capability index, a multi-objective route optimization model is constructed to obtain comprehensive decision indicators;

[0011] Dynamic path planning is performed based on the environmental risk index, the resource response capability index, and the comprehensive decision-making index to obtain the path optimization coefficient;

[0012] Based on the environmental risk index, the resource response capability index, the comprehensive decision index, and the path optimization coefficient, the final decision index is calculated, and emergency response decisions are executed based on the final decision index.

[0013] Optionally, calculating the environmental risk index of the sea area where the ship oil spill occurred based on the preprocessed multi-source data includes:

[0014] The wave height, wind speed, air pressure, visibility, water flow speed, and precipitation at a preset time are extracted from the multi-source data.

[0015] Obtain the ship density and waterway congestion in the area where the ship oil spill occurred, based on preset coordinates.

[0016] The environmental risk index is determined based on the wave height, wind speed, air pressure, visibility, water flow speed, and precipitation in the sea area where the ship oil spill occurred at a preset time, as well as the ship density and waterway congestion in the area where the preset coordinate point is located.

[0017] Optionally, the environmental risk index is expressed as:

[0018] ;

[0019] in, It is a comprehensive environmental risk index. It is the wave height at time t. It is the wind speed at time t. It is the air pressure at time t. It is the visibility at time t. It is the water flow velocity at time t. It is the precipitation at time t. Coordinates Ship density in the area Coordinates The waterway congestion level in the area These are the first weight, the second weight, and the third weight, respectively.

[0020] Optionally, the assessment of emergency resource allocation capability based on the environmental risk index to obtain the resource response capability index includes:

[0021] Obtain the coordinates of the oil spill incident, the location of the supplies, and the maximum permissible response time for making emergency response decisions;

[0022] Determine the straight-line distance from the accident coordinate point to the material storage point;

[0023] Determine the estimated transportation time of the materials from the accident coordinates to the material storage point;

[0024] Obtain the status of each means of transport and the reserve quantity of each of the aforementioned material storage points;

[0025] The resource response capability index is determined based on the status of each of the transport vehicles, the reserve quantity of each of the material reserve points, the environmental risk index, the maximum permissible response time, the distance from the accident coordinate point to the material reserve point, and the estimated transportation time of the materials from the accident coordinate point to the material reserve point.

[0026] Optionally, the resource responsiveness index is expressed as:

[0027] ;

[0028] in, It is a resource responsiveness index. It is the reserve quantity of the i-th material reserve point. This is the state of the j-th means of transport. The accident coordinates The straight-line distance to the material storage point. This is the estimated transportation time for supplies from the accident coordinates (x, y) to the supply storage point. This is the maximum allowed response time. It is the fourth weight. It is the fifth weight.

[0029] Optionally, the comprehensive decision index obtained by constructing a multi-objective route optimization model based on the environmental risk index and the resource response capability index includes:

[0030] Obtain baseline route length and standard fuel consumption;

[0031] Obtain the actual route length from the accident coordinates to the material storage point, and the actual fuel consumption of the transport vehicle within the actual route length;

[0032] Based on the environmental risk index, the resource response capability index, the baseline route length, the standard fuel consumption, the actual route length, and the actual fuel consumption, a multi-objective route optimization model is constructed, and the comprehensive decision index is determined based on the multi-objective route optimization model.

[0033] Optionally, the step of performing dynamic path planning based on the environmental risk index, the resource response capability index, and the comprehensive decision-making index to obtain path optimization coefficients includes:

[0034] Obtain the environmental risk index for each transit point along the route;

[0035] Obtain the time decay coefficient, which characterizes the degree of decay of the resource responsiveness index over time;

[0036] Dynamic path planning is performed based on the environmental risk index, the resource response capability index, the comprehensive decision-making index, the environmental risk index, and the time decay coefficient to determine the path optimization coefficient.

[0037] Optionally, the step of calculating the final decision index based on the environmental risk index, the resource response capability index, the comprehensive decision index, and the path optimization coefficient includes:

[0038] Obtain the maximum allowed response time;

[0039] The comprehensive decision-making index is adjusted based on the maximum allowable response time to obtain the adjusted comprehensive decision-making index;

[0040] The final decision index is calculated based on the environmental risk index, the resource response capability index, the adjusted comprehensive decision index, and the path optimization coefficient.

[0041] Optionally, the method further includes:

[0042] When the value exceeds the first threshold, the emergency response decision corresponding to the final decision indicator is executed immediately.

[0043] When the value is less than or equal to the first threshold and greater than or equal to the second threshold, the emergency response decision corresponding to the final decision indicator is adjusted to obtain an adjustment decision, and then the adjustment decision is executed.

[0044] When the value is less than the second threshold, the emergency response decision corresponding to the final decision indicator is discarded, and a new decision is made for the oil spill.

[0045] This invention also provides a ship oil spill emergency response decision-making system based on multi-source data fusion, the system comprising:

[0046] The data processing module is used to collect multi-source data related to ship oil spill emergency response decision-making, and to preprocess the multi-source data to obtain preprocessed multi-source data; the multi-source data includes real-time sea state data, meteorological data, maritime traffic data, and emergency resource data;

[0047] The environmental risk module is used to calculate the environmental risk index of the sea area where the ship oil spill occurred based on the preprocessed multi-source data.

[0048] The response capability module is used to assess the emergency resource allocation capability based on the environmental risk index and obtain the resource response capability index.

[0049] The decision index module is used to construct a multi-objective route optimization model based on the environmental risk index and the resource response capability index to obtain comprehensive decision indexes;

[0050] The path optimization module is used to perform dynamic path planning based on the environmental risk index, the resource response capability index, and the comprehensive decision-making index to obtain path optimization coefficients.

[0051] The response decision module is used to calculate the final decision index based on the environmental risk index, the resource response capability index, the comprehensive decision index and the path optimization coefficient, and to execute emergency response decisions based on the final decision index.

[0052] Furthermore, to achieve the above objectives, the present invention also proposes an electronic device, comprising: a memory for storing computer software programs; and a processor for reading and executing the computer software programs, thereby realizing the ship oil spill emergency response decision-making method based on multi-source data fusion as described above.

[0053] Furthermore, to achieve the above objectives, the present invention also proposes a non-transitory computer-readable storage medium storing a computer software program, which, when executed by a processor, implements a ship oil spill emergency response decision-making method based on multi-source data fusion as described above.

[0054] The beneficial effects of this invention are:

[0055] (1) This invention employs a decision-making method based on multi-source data fusion. By comprehensively considering real-time information on sea state data, meteorological data, maritime traffic conditions, and emergency resources, it effectively improves the accuracy of decision-making. The fusion of different data sources can provide decision-makers with comprehensive environmental information, thereby helping to formulate scientific and reasonable emergency response plans and avoiding decision-making errors caused by insufficient or biased information.

[0056] (2) By introducing the Environmental Risk Assessment Index (ERI), this invention can comprehensively assess the potential impact of changes in marine environmental conditions (such as wave height, wind speed, water flow, precipitation, visibility, etc.) on oil spill emergency response. This comprehensive risk assessment can reflect the impact of sudden environmental conditions on the accident handling process in real time, helping decision-makers to take effective preventive measures in advance and reduce the risk of environmental pollution and damage.

[0057] (3) This invention assesses the ability to allocate emergency resources by designing a Resource Response Capability Index (RCI), which comprehensively considers factors such as material reserves, transportation vehicle status, and resource arrival time. Using this assessment, it is possible to ensure the rapid and efficient allocation of emergency resources under limited conditions, improve emergency response efficiency, and reduce delays caused by resource shortages or improper allocation.

[0058] In summary, this invention, through the introduction of a series of innovative measures such as multi-source data fusion, environmental risk assessment, resource allocation optimization, route planning, and dynamic adjustment, achieves scientific decision-making and optimization in ship oil spill emergency response. Its beneficial effects are not only reflected in improved decision-making accuracy, optimized resource utilization, and reduced costs, but also in enhancing the timeliness, flexibility, and sustainability of emergency response, enabling oil spill emergency response to be conducted more efficiently, safely, and environmentally friendly. Attached Figure Description

[0059] Figure 1 A flowchart of a ship oil spill emergency response decision-making method based on multi-source data fusion provided by the present invention;

[0060] Figure 2 A schematic diagram of the structure of a ship oil spill emergency response decision system based on multi-source data fusion provided by the present invention;

[0061] Figure 3 A schematic diagram of the hardware structure of a possible electronic device provided by the present invention;

[0062] Figure 4 This is a schematic diagram of the hardware structure of a possible computer-readable storage medium provided by the present invention. Detailed Implementation

[0063] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0064] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0065] In the description of this invention, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed herein.

[0066] Please see Figure 1 The present invention provides a flowchart of a ship oil spill emergency response decision-making method based on multi-source data fusion, including the following steps:

[0067] Step 201: Collect multi-source data related to ship oil spill emergency response decision-making, and preprocess the multi-source data to obtain preprocessed multi-source data.

[0068] Multi-source data can include real-time sea condition data, meteorological data, maritime traffic data, and emergency resource data.

[0069] Specifically, the collection and preprocessing of multi-source data are crucial steps in ensuring the scientific rigor and accuracy of emergency response decisions. By collecting and processing different types of data in real time, a high-quality information foundation can be provided for subsequent decisions such as environmental risk assessment, resource allocation optimization, and route planning. Preprocessing of multi-source data is key to improving data quality, aiming to eliminate noise, standardize data formats, and ensure that the data is usable for subsequent analysis and decision-making.

[0070] Real-time sea state data is crucial for describing the marine environment, typically including variables such as wave height, wind speed, and current velocity. This data reflects the dynamic conditions on the sea surface and significantly impacts the spread of oil spills, the difficulty of emergency response, and safety. Sea state data can be acquired in real time using marine monitoring equipment (such as buoys, satellite remote sensing, and ship-borne sensors). These devices can obtain real-time data on dynamic changes in waves, wind speed, and currents. Sea state data directly affects the speed and extent of oil spill spread; higher wave height, wind speed, and current velocity generally lead to a greater speed and extent of oil spill spread, and a more challenging emergency response.

[0071] Meteorological data, including variables such as visibility, precipitation, and air pressure, describes atmospheric conditions in the marine environment. Meteorological conditions are an indispensable factor in oil spill emergency response, affecting ship navigation, visibility of rescue operations, and the speed of oil spill spread. Meteorological data can be obtained through weather stations, satellite remote sensing, and weather forecasting systems. It includes information such as temperature, air pressure, humidity, and precipitation, and is provided in real time according to different needs. Severe weather (such as strong winds, low visibility, and precipitation) increases the difficulty of emergency response, affecting the efficiency of oil spill cleanup and the safety of rescue missions. Meteorological conditions have a direct impact on ship navigation, oil spill spread, and the deployment of rescue teams.

[0072] Maritime traffic data, including information such as vessel density and channel congestion, reflects the flow and intensity of maritime traffic. This type of data helps assess vessel activity near an accident site and the difficulty of dispatching emergency resources. Maritime traffic data can be collected in real time through AIS (Automatic Identification System), ship radar, and maritime monitoring systems. These systems provide data on vessel positions, speeds, routes, and density. Vessel density and channel congestion affect the dispatch of emergency resources. Dense vessel traffic and congested channels increase the complexity of emergency response, making resource allocation and route planning more difficult.

[0073] Emergency resource data refers to information such as the quantity of supplies needed for oil spill emergency response, the status of transportation vehicles, and personnel allocation. This includes the status and distribution of oil-absorbing materials, rescue equipment, and transport vessels. Emergency resource data is typically provided by emergency management departments, maritime rescue teams, or material reserve systems, and is monitored and updated in real time through information systems. Emergency resource data directly impacts response speed and efficiency. When resources are sufficient and transportation vehicles are in good condition, an emergency response can be launched rapidly. Conversely, resource shortages or poor transportation vehicle status will delay response time and may even affect the safety of rescue operations.

[0074] In some embodiments, the goal of preprocessing multi-source data is to transform different types of data into a uniform format and perform steps such as noise reduction, missing value imputation, and standardization to ensure data quality and the usability of subsequent analysis.

[0075] In summary, by collecting and preprocessing multi-source data (such as sea state data, meteorological data, maritime traffic data, and emergency resource data), this invention can provide comprehensive and accurate information support for oil spill emergency response. The preprocessing process includes data cleaning, format standardization, fusion, and deduplication steps to ensure data quality and processing efficiency. High-quality multi-source data input provides a solid data foundation for decisions such as environmental risk assessment, resource allocation, and route optimization, thereby ensuring the efficiency and scientific nature of the emergency response.

[0076] Step 202: Based on the preprocessed multi-source data, calculate the environmental risk index of the sea area where the ship oil spill occurred.

[0077] In some embodiments, step 202 may include:

[0078] The wave height, wind speed, air pressure, visibility, water flow speed, and precipitation at a preset time are extracted from the multi-source data.

[0079] Obtain the ship density and waterway congestion in the area where the ship oil spill occurred, based on preset coordinates.

[0080] The environmental risk index is determined based on the wave height, wind speed, air pressure, visibility, water flow speed, and precipitation in the sea area where the ship oil spill occurred at a preset time, as well as the ship density and waterway congestion in the area where the preset coordinate point is located.

[0081] In some embodiments, the environmental risk index can be expressed as:

[0082] ;

[0083] in, It is a comprehensive environmental risk index. It is the wave height at time t. It is the wind speed at time t. It is the air pressure at time t. It is the visibility at time t. It is the water flow velocity at time t. It is the precipitation at time t. Coordinates Ship density in the area Coordinates The waterway congestion level in the area These are the first weight, the second weight, and the third weight, respectively.

[0084] In the specific implementation, Wave height reflects the undulation of the sea surface and is a crucial factor affecting the speed of oil spill spread and the difficulty of cleanup. Higher wave heights indicate more severe sea conditions, potentially leading to a wider oil spill spread and increased challenges to emergency response.

[0085] Wind speed is another important factor affecting the spread of oil spills. The higher the wind speed, the faster the oil is blown away, and the wider the spread will be.

[0086] and These two parameters act as constraints. Air pressure affects wind speed and climate change; wind speed may increase in low-pressure environments. Visibility directly affects the visibility of rescue operations; the lower the visibility, the less efficient the search and rescue and emergency resource deployment, increasing the complexity of the response.

[0087] This part of the formula calculates the interrelationships between wave height, wind speed, air pressure, and visibility, using weighting coefficients. Adjustments were made to reflect the impact of these climatic factors on the environmental risks of the oil spill. This impact is primarily reflected in changes in marine climate, especially in severe weather conditions, where sea surface conditions and visibility directly affect the difficulty and efficiency of emergency response.

[0088] Water flow speed directly affects how quickly oil spills spread on the water surface. The faster the water flow, the faster the oil spills spread, and the wider the potential risk area.

[0089] Rainfall affects the dilution and dissolution of oil spills on the sea surface. In cases of heavy rainfall, oil spills may be diluted and mixed with the water, affecting the cleanup of oil spills.

[0090] This section represents the impact of environmental mobility factors by multiplying water flow velocity by precipitation. The exponentiation emphasizes the nonlinear influence of water flow and precipitation on oil spill dispersion. Due to the significant variations in water flow and precipitation, weighting coefficients are used. The higher-order equations are used to emphasize their risk impact on emergency response decisions.

[0091] Coordinates The ship density in a given area reflects the concentration of ships within that area. Excessive density increases the risk of collisions or traffic accidents between ships and may hinder the rapid entry and operation of emergency response teams.

[0092] Channel congestion is an indicator of channel capacity. Severe congestion can slow down the movement of ships and affect the efficiency of resource and personnel deployment in oil spill incidents.

[0093] This section calculates the ratio of ship density to channel congestion and then uses an exponential function for weighting. High ship density and channel congestion lead to a sharp increase in risk because these factors limit the timeliness and effectiveness of emergency response. This section... The weights were adjusted, and the nonlinear impact of ship density and congestion on environmental risk was reinforced through exponential relationships.

[0094] Each weight controls the relative importance of each factor in the comprehensive environmental risk assessment. By adjusting these coefficients, the degree of influence of each factor can be flexibly adjusted according to specific environmental conditions. The contribution of wave height and wind speed to environmental risk. The contribution of controlling water flow and precipitation to risk. The contribution of vessel density and waterway congestion to risk is controlled. The three weights are added together to equal 1, ensuring that the weight sum of the entire assessment formula is 1, thus maintaining a balance in risk assessment across all factors.

[0095] The Environmental Risk Index (ERI) comprehensively considers multiple factors, including marine meteorological conditions, ocean mobility, traffic conditions, and ship activities. A higher ERI value indicates greater risk and greater difficulty in emergency response. The ERI provides a scientific basis for emergency response decision-making. It helps decision-makers identify the most dangerous marine conditions and provides a reference for resource allocation, route planning, and mission execution. By calculating the ERI, the environmental complexity of an oil spill can be quickly assessed, thereby enabling the development of response strategies.

[0096] In summary, the Environmental Risk Assessment Index (ERI) of this invention provides a numerical indicator that dynamically reflects the correlation between the current environmental situation and oil spill emergency response through comprehensive calculation of multiple environmental factors. By weighting key factors such as wave height, wind speed, air pressure, visibility, water flow velocity, precipitation, ship density, and waterway congestion, the ERI can effectively assess the current environmental risk and provide theoretical support for emergency response decisions.

[0097] Step 203: Assess emergency resource allocation capabilities based on the environmental risk index to obtain the resource response capability index.

[0098] In some embodiments, step 203 may include:

[0099] Obtain the coordinates of the oil spill incident, the location of the supplies, and the maximum permissible response time for making emergency response decisions;

[0100] Determine the straight-line distance from the accident coordinate point to the material storage point;

[0101] Determine the estimated transportation time of the materials from the accident coordinates to the material storage point;

[0102] Obtain the status of each means of transport and the reserve quantity of each of the aforementioned material storage points;

[0103] The resource response capability index is determined based on the status of each of the transport vehicles, the reserve quantity of each of the material reserve points, the environmental risk index, the maximum permissible response time, the distance from the accident coordinate point to the material reserve point, and the estimated transportation time of the materials from the accident coordinate point to the material reserve point.

[0104] In some embodiments, the resource responsiveness index can be expressed as:

[0105] ;

[0106] in, It is a resource responsiveness index. It is the reserve quantity of the i-th material reserve point. This is the state of the j-th means of transport. The accident coordinates The straight-line distance to the material storage point. This is the estimated transportation time for supplies from the accident coordinates (x, y) to the supply storage point. This is the maximum allowed response time. It is the fourth weight. It is the fifth weight.

[0107] In the specific implementation, This represents the reserve quantity at different material storage points. Here, 'i' represents the index of the material storage point (e.g., oil absorbent materials, emergency equipment, etc.). The larger the material reserve quantity, the more resources can be provided in an oil spill event, thereby improving response capabilities.

[0108] This indicates the status of the transportation vehicle. Here, j represents the index of the transportation vehicle (e.g., emergency boats, transport vehicles, etc.). If the transportation vehicle is in good condition and has a large carrying capacity, emergency supplies can be delivered more quickly. Therefore, A larger value indicates that resources can be quickly allocated and transported.

[0109] This section illustrates the direct relationship between material reserves and transportation vehicles; the quantity of material reserves and the condition of transportation vehicles directly determine the potential for emergency response. Through multiplication, the synergistic capability between material reserves and transportation vehicles can be quantified.

[0110] Indicates the coordinates of the accident. The straight-line distance to the material storage point. The shorter the straight-line distance, the lower the time cost of material allocation and transportation, and the faster the response speed. Conversely, when the distance is long, the time and resources required for transportation will increase, and the efficiency of emergency response will decrease.

[0111] The Environmental Risk Assessment Index (ERI) reflects the complexity and difficulty of emergency response posed by current marine environmental conditions. A higher ERI value indicates greater environmental risk and increased difficulty in response. Therefore, distant material storage sites and areas with higher environmental risks will correspondingly increase the complexity of the response.

[0112] This section takes into account both distance and environmental risks, and calculates the impact of distance and environmental complexity between material storage points and the accident site. Longer distances or higher environmental risks significantly increase the difficulty and time required for emergency response. Therefore, this section reflects the negative impact of distance and environmental risks on resource allocation efficiency through a weighted approach.

[0113] Indicates from the accident coordinate point The estimated transport time to the material storage point. A longer estimated transport time means a delay in emergency response, affecting the timeliness of accident handling. This indicates the maximum permissible response time, i.e., the upper limit of the specified emergency response time. If the actual transportation time... If this limit is exceeded, the response will be considered invalid or unqualified. Therefore, controlling transit time is crucial for improving responsiveness.

[0114] The impact of transportation time is attenuated. The closer the response time is to the maximum permissible response time, the smaller the exponent value, leading to a decrease in the RCI value; conversely, when the response time is shorter, the exponent value is larger, and the RCI value is higher. This part reflects the impact of transportation time on emergency response capability. If the expected transportation time is too long, exceeding the maximum permissible response time, the exponential attenuation causes the RCI value to drop rapidly, indicating a significant reduction in resource response capability, and decision-makers need to adjust the emergency plan.

[0115] It is the fourth weight. This is the fifth weighting, adjusting the relative importance of material reserves and vehicle condition in the RCI. This is achieved through adjustment... This can emphasize or downplay the impact of the status of resource reserves and transportation vehicles on emergency response capabilities. The importance of transit time in RCI can be adjusted, with larger [measures]. The value indicates that transportation time is considered more important to response capability. Adjusting the parameters of the model's flexibility allows for the adjustment of the contribution ratio of different factors in the RCI according to actual needs, thereby reflecting the priority factors for emergency response in different scenarios.

[0116] The Resource Allocation Index (RCI) is a comprehensive index used to measure the overall resource allocation capacity and efficiency of an emergency response system. A higher RCI value indicates a stronger capacity for allocating emergency resources, including material reserves and transportation scheduling, enabling a faster and more effective response to oil spills. By calculating the RCI, decision-makers can assess current resource response capabilities and determine whether further optimization of resource allocation, transportation scheduling, or response strategies is needed. A low RCI value may necessitate optimizing the location of material storage points, improving the availability of transportation vehicles, or shortening transportation times.

[0117] In summary, the RCI (Resource Response Capability Index) of this invention quantifies the ability to allocate emergency response resources by comprehensively assessing factors such as material reserves, vehicle condition, distance, environmental risks, and transportation time. This index is designed to help decision-makers identify and optimize resource allocation, ensuring that resources can be rapidly and effectively deployed during oil spill emergency responses, thereby improving the efficiency and timeliness of emergency response.

[0118] Step 204: Based on the environmental risk index and the resource response capability index, construct a multi-objective route optimization model to obtain comprehensive decision indicators.

[0119] In some embodiments, step 204 may include:

[0120] Obtain baseline route length and standard fuel consumption;

[0121] Obtain the actual route length from the accident coordinates to the material storage point, and the actual fuel consumption of the transport vehicle within the actual route length;

[0122] Based on the environmental risk index, the resource response capability index, the baseline route length, the standard fuel consumption, the actual route length, and the actual fuel consumption, a multi-objective route optimization model is constructed, and the comprehensive decision index is determined based on the multi-objective route optimization model.

[0123] In some embodiments, the comprehensive decision-making index can be expressed as:

[0124] ;

[0125] in, It is a comprehensive decision-making indicator. The accident coordinates The actual flight path length to the supply depot It is the baseline route length. This is the standard fuel consumption. This is the actual fuel consumption. It is the sixth weight. It is the seventh weight. It is the eighth weight.

[0126] In practice, RCI is an indicator used to assess the ability to allocate emergency resources. The higher the RCI value, the stronger the response capability of material reserves and transportation vehicles, and the more quickly resources can be dispatched for emergency response.

[0127] ERI measures the impact of current environmental conditions on emergency response. The higher the ERI value, the greater the environmental risk, and the more difficult the emergency response becomes.

[0128] Control the degree of influence of RCI and ERI on the comprehensive decision indicators. The weights of resource responsiveness and environmental risk in route selection were determined. Larger... The value indicates a greater focus on resource responsiveness and environmental risks, and optimization will place greater emphasis on balancing these two factors.

[0129] This section comprehensively considers the impact of resource responsiveness and environmental risk by weighting the combination of RCI and ERI. By converting the negative impact of environmental risks from a range of 0 to 1, the optimization objective becomes more inclined to choose paths that can reduce environmental risks when environmental risks increase.

[0130] Indicates from the accident coordinate point The actual length of the flight route to the supply depot. The longer the actual flight route, the farther the transportation distance, and the more time and resources are required. This is the baseline route length, typically the shortest path from the accident point to the target point. This length is a standard value representing the length of the optimal route. The importance of controlling flight path length in comprehensive decision-making. (Larger) The value indicates a greater focus on path length, and shorter routes will be prioritized during optimization.

[0131] This section measures the impact of route length on emergency response efficiency by calculating the ratio of the actual route length to the baseline route length. A longer actual route length means higher transportation time and resource consumption, resulting in a lower contribution to overall decision-making indicators. During optimization, a preference will be given to choosing shorter routes to save resources.

[0132] This is standard fuel consumption, typically the expected fuel consumption under standard sailing conditions. It represents the amount of fuel required for sailing under ideal conditions. This is actual fuel consumption, representing the amount of fuel consumed during actual navigation, depending on environmental conditions and route selection. The impact of fuel consumption control on overall decision-making indicators. Significant. The value indicates a greater focus on fuel consumption, and optimization will tend to reduce fuel consumption.

[0133] This section measures the impact of route optimization on fuel use by calculating the ratio of standard fuel consumption to actual fuel consumption. Lower fuel consumption indicates more optimized route selection, which reduces costs during emergency response. If actual fuel consumption is close to the standard value, it means the route selection is efficient and the optimization effect is good.

[0134] The entire expression is integrated to represent the cumulative impact on each decision factor over a certain time frame (potentially the entire emergency response process). Integration allows the effects of time variations on each decision factor to be considered during optimization, enabling decisions to dynamically adapt to changes in the emergency environment. By integrating, the influence of various time-varying factors during emergency response can be captured, making decisions more dynamic and adaptable to real-time changing environmental conditions.

[0135] CDI (Combined Response Index) is a comprehensive decision-making indicator that combines multiple factors such as resource responsiveness, environmental risk, route length, and fuel consumption. It reflects the efficiency of optimized route selection and emergency response. A higher CDI value indicates a better optimized solution, meaning the selected path, after comprehensively considering factors such as time, resources, and the environment, reduces risk while improving resource utilization efficiency. By calculating CDI, decision-makers can choose the optimal path from multiple options. CDI helps decision-makers meet emergency response needs while minimizing time, cost, and environmental risks, achieving optimal allocation of emergency resources. The design of CDI considers multiple optimization objectives, such as resource responsiveness, time, route length, and fuel consumption. By adjusting the weighting coefficients, the priority of optimization objectives can be flexibly adjusted according to different emergency scenarios, ensuring that the emergency response plan is both efficient and economical.

[0136] In summary, the Comprehensive Decision Index (CDI) of this invention helps decision-makers select the optimal path by weighting multiple factors (resource responsiveness, environmental risk, route length, fuel consumption, etc.). The design of CDI enables emergency response decisions to balance different objectives, such as time, resources, cost, and environmental risk, thereby providing a comprehensive and scientific basis for emergency response decisions. In practical applications, CDI can dynamically adjust decisions, optimize emergency response processes, and improve response efficiency and resource utilization.

[0137] Step 205: Perform dynamic path planning based on the environmental risk index, the resource response capability index, and the comprehensive decision-making index to obtain the path optimization coefficient.

[0138] In some embodiments, step 205 may include:

[0139] Obtain the environmental risk index for each transit point along the route;

[0140] Obtain the time decay coefficient, which characterizes the degree of decay of the resource responsiveness index over time;

[0141] Dynamic path planning is performed based on the environmental risk index, the resource response capability index, the comprehensive decision-making index, the environmental risk index, and the time decay coefficient to determine the path optimization coefficient.

[0142] In some embodiments, the path optimization coefficient can be expressed as:

[0143] ;

[0144] in, Here, k is the path optimization coefficient, and k is the time decay coefficient. The environmental risk index for the i-th transfer point on the route. It is the ninth weight. It is the tenth weight. It is the eleventh weight.

[0145] In practice, CDI (Critical Displacement Index) is a key indicator for multi-objective optimization, integrating factors such as fuel consumption, route length, and resource responsiveness. A higher CDI value indicates a better overall route decision. RCI (Resource Capability Index) assesses the ability to allocate emergency resources, reflecting the effectiveness of resource allocation. A higher RCI value indicates stronger resource allocation capabilities and a faster response. The k-time decay coefficient controls the degree to which the impact of RCI on route optimization decays over time. As time progresses, the impact of RCI on route selection gradually decreases, indicating that as the emergency response process advances, resource allocation efficiency gradually becomes a secondary factor influencing route selection.

[0146] This section, through a weighted combination of CDI and RCI, comprehensively considers the decision-making efficiency and resource allocation capabilities of flight routes, and through... Adjustments are made to the impact of time, enabling flexible route selection based on changes in resource allocation capabilities during route optimization.

[0147] This represents the environmental risk of the i-th transit point on the route. A higher ERI value indicates a greater environmental risk at that point and a greater impact on emergency response. The environmental risk of each transit point is taken into account, especially the potential impact on ship navigation safety and oil spill spread. The product operation is used to combine the environmental risk indices of each transit point into a single index, representing the environmental risk of the entire route. High environmental risk at each transit point will lead to a decrease in the optimization index of the entire route, ultimately affecting route selection.

[0148] This section reflects the impact of environmental risk at each transit point on the overall route optimization through a product relationship. The higher the environmental risk at each transit point, the worse the route optimization effect, and vice versa. The introduction of this section emphasizes the importance of environmental risk in route selection; in high-risk areas, route selection optimization will be more cautious.

[0149] This is the maximum permissible response time, which is the latest time limit for emergency response. If the emergency response exceeds this time, the optimal emergency window may be missed, leading to a wider spread of oil spills and more severe pollution. The estimated transport time from the accident site to the supply depot or other critical location. The shorter the transport time, the faster the emergency response and the better the route selection.

[0150] This section reflects the impact of transit time on route selection. The ratio of the maximum response time to the actual transit time ensures that the emergency response time does not exceed the set maximum response time. If the transit time is too long, the Point of Interest (POI) value will drop significantly, forcing the optimization scheme to prioritize shorter routes, thereby ensuring that the emergency response is completed in the shortest possible time.

[0151] The ninth weight modifies the influence of the Comprehensive Decision Index (CDI) and the Resource Response Index (RCI) in route optimization. This weight controls the trade-off between decision-making efficiency and resource allocation capability in route selection. The tenth weight controls the impact of the Environmental Risk Index on route optimization. This weight determines the importance of environmental risk in the overall route optimization process. Higher environmental risks result in a stronger weight for this item, forcing more cautious route selection. The eleventh weight modifies the weight of transit time in route optimization. This weight determines the relative importance of emergency response time in route selection, ensuring that emergency responses are completed within the stipulated timeframe as much as possible.

[0152] Step 206: Calculate the final decision index based on the environmental risk index, the resource response capability index, the comprehensive decision index, and the path optimization coefficient, and execute the emergency response decision based on the final decision index.

[0153] In some embodiments, step 206 may include:

[0154] Obtain the maximum allowed response time;

[0155] The comprehensive decision-making index is adjusted based on the maximum allowable response time to obtain the adjusted comprehensive decision-making index;

[0156] The final decision index is calculated based on the environmental risk index, the resource response capability index, the adjusted comprehensive decision index, and the path optimization coefficient.

[0157] In some embodiments, the final decision metric can be expressed as:

[0158] ;

[0159] in, This is the final decision indicator, used only as an example. Assuming the first threshold is 0.8 and the second threshold is 0.5, then if FDI>0.8, the plan will be implemented immediately; if 0.5≤FDI≤0.8, the plan needs to be adjusted; if FDI<0.5, the plan needs to be re-formulated.

[0160] In practice, executing emergency response decisions is the final step in the entire emergency response system. The key is to determine, based on previously calculated Final Decision Indicators (FDI), whether to immediately implement the emergency response plan or whether adjustments and reformulation are needed. The purpose of this stage is to ensure that the emergency response can be carried out efficiently and promptly, minimizing environmental pollution and economic losses caused by the oil spill.

[0161] The process of implementing emergency response decisions relies on the calculation of various indicators, especially parameters related to comprehensive decision-making (such as the Environmental Risk Index (ERI), Resource Response Capability Index (RCI), and Comprehensive Decision Index (CDI). Specifically, the Final Decision Index (FDI) is the output of the entire decision-making chain, and decision-makers will take different actions depending on the FDI value.

[0162] When FDI exceeds the first threshold of 0.8, it indicates that, based on calculations of current environmental risks, resource response capabilities, and path optimization, the current emergency response plan performs well in terms of efficiency, timeliness, and feasibility, meeting the conditions for rapid activation. In this scenario, the emergency response plan can be executed immediately. Emergency resources will be rapidly mobilized, with ships, rescue teams, and cleanup equipment quickly entering the accident site to clean up and control the oil spill. The goal is to control the spread of oil pollution in the shortest possible time and reduce further environmental damage.

[0163] When FDI is between the first and second thresholds, for example, between 0.5 and 0.8, it indicates that while the current solution is executable, there is still room for optimization. There may be issues such as insufficient resource allocation, suboptimal path design, or high environmental risks. This means that although an emergency response can be initiated, its effectiveness may not be as expected, and dynamic adjustments may be necessary during execution.

[0164] When FDI falls below the second threshold of 0.5, it indicates significant problems with the current emergency response plan, such as insufficient resource allocation, excessive environmental risk, or inappropriate route selection. This could lead to excessively long response times or wasted resources, ultimately failing to effectively control the oil spill. In this case, the effectiveness of the emergency response plan will be greatly reduced, and it may even have negative consequences. The plan should be immediately revised. This may require reassessing resource conditions, adjusting response strategies, and even changing key emergency response decisions, such as selecting new routes, reallocating emergency resources, or designing new plans based on new environmental changes. Revising the plan may also include adjusting the maximum response time or improving the Environmental Risk Assessment (ERI).

[0165] The core of this invention for emergency response decision-making lies in using the Final Decision Index (FDI) to assess the feasibility and timeliness of emergency response plans, and determining whether to immediately implement, adjust, or revise the plan based on the FDI value. Through a comprehensive assessment of environmental risks, resource response capabilities, pathway optimization, and integrated decision-making, it ensures that emergency responses are implemented efficiently, promptly, and accurately, minimizing the environmental impact and economic losses caused by accidents.

[0166] Please see Figure 2 , Figure 2 This is a schematic diagram of the structure of a ship oil spill emergency response decision system based on multi-source data fusion, provided by the present invention.

[0167] like Figure 2 As shown in the figure, the ship oil spill emergency response decision system based on multi-source data fusion proposed in this embodiment of the invention includes:

[0168] The data processing module 301 is used to collect multi-source data related to ship oil spill emergency response decision-making, and to preprocess the multi-source data to obtain preprocessed multi-source data; the multi-source data includes real-time sea state data, meteorological data, maritime traffic data, and emergency resource data.

[0169] Environmental risk module 302 is used to calculate the environmental risk index of the sea area where the ship oil spill occurred based on the preprocessed multi-source data;

[0170] The response capability module 303 is used to assess the emergency resource allocation capability based on the environmental risk index and obtain the resource response capability index.

[0171] The decision index module 304 is used to construct a multi-objective route optimization model based on the environmental risk index and the resource response capability index to obtain comprehensive decision indexes;

[0172] The path optimization module 305 is used to perform dynamic path planning based on the environmental risk index, the resource response capability index and the comprehensive decision-making index to obtain the path optimization coefficient.

[0173] The response decision module 306 is used to calculate the final decision index based on the environmental risk index, the resource response capability index, the comprehensive decision index and the path optimization coefficient, and to execute emergency response decisions based on the final decision index.

[0174] Please see Figure 3 , Figure 3 This is a schematic diagram illustrating an embodiment of the electronic device provided in this invention. For example... Figure 3 As shown, an embodiment of the present invention provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, it performs the following steps:

[0175] Collect multi-source data related to ship oil spill emergency response decision-making, and preprocess the multi-source data to obtain preprocessed multi-source data; the multi-source data includes real-time sea state data, meteorological data, maritime traffic data, and emergency resource data;

[0176] Based on the preprocessed multi-source data, the environmental risk index of the sea area where the oil spill occurred is calculated.

[0177] Based on the aforementioned environmental risk index, the emergency resource allocation capability is assessed to obtain the resource response capability index.

[0178] Based on the environmental risk index and the resource response capability index, a multi-objective route optimization model is constructed to obtain comprehensive decision indicators;

[0179] Dynamic path planning is performed based on the environmental risk index, the resource response capability index, and the comprehensive decision-making index to obtain the path optimization coefficient;

[0180] Based on the environmental risk index, the resource response capability index, the comprehensive decision index, and the path optimization coefficient, the final decision index is calculated, and emergency response decisions are executed based on the final decision index.

[0181] Please see Figure 4 , Figure 4 This is a schematic diagram illustrating an embodiment of a computer-readable storage medium provided by an embodiment of the present invention. For example... Figure 4 As shown, this embodiment provides a computer-readable storage medium 500 on which a computer program 411 is stored. When the computer program 411 is executed by a processor, it performs the following steps:

[0182] Collect multi-source data related to ship oil spill emergency response decision-making, and preprocess the multi-source data to obtain preprocessed multi-source data; the multi-source data includes real-time sea state data, meteorological data, maritime traffic data, and emergency resource data;

[0183] Based on the preprocessed multi-source data, the environmental risk index of the sea area where the oil spill occurred is calculated.

[0184] Based on the aforementioned environmental risk index, the emergency resource allocation capability is assessed to obtain the resource response capability index.

[0185] Based on the environmental risk index and the resource response capability index, a multi-objective route optimization model is constructed to obtain comprehensive decision indicators;

[0186] Dynamic path planning is performed based on the environmental risk index, the resource response capability index, and the comprehensive decision-making index to obtain the path optimization coefficient;

[0187] Based on the environmental risk index, the resource response capability index, the comprehensive decision index, and the path optimization coefficient, the final decision index is calculated, and emergency response decisions are executed based on the final decision index.

[0188] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0189] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0190] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A system that specifies functions in one or more boxes.

[0191] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including an instruction set implemented in a process. Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0192] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0193] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0194] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A decision-making method for emergency response to ship oil spills based on multi-source data fusion, characterized in that, The method includes: Collect multi-source data related to ship oil spill emergency response decision-making, and preprocess the multi-source data to obtain preprocessed multi-source data; the multi-source data includes real-time sea state data, meteorological data, maritime traffic data, and emergency resource data; Based on the preprocessed multi-source data, the environmental risk index of the sea area where the ship oil spill occurred is calculated, including: extracting wave height, wind speed, air pressure, visibility, water flow speed, and precipitation at a preset time from the multi-source data; obtaining the ship density and channel congestion in the area where the preset coordinate point is located within the sea area where the ship oil spill occurred; and determining the environmental risk index based on the wave height, wind speed, air pressure, visibility, water flow speed, and precipitation at the preset time in the sea area where the ship oil spill occurred, as well as the ship density and channel congestion in the area where the preset coordinate point is located. The resource response capability index is obtained by assessing the emergency resource allocation capability based on the environmental risk index, including: obtaining the coordinates of the accident where the oil spill occurred, the material storage point where the materials are located, and the maximum allowable response time for making emergency response decisions; determining the straight-line distance from the accident coordinates to the material storage point; determining the estimated transportation time of the materials from the material storage point to the accident coordinates; obtaining the status of each means of transport and the reserve quantity at each material storage point; and determining the resource response capability index based on the status of each means of transport, the reserve quantity at each material storage point, the environmental risk index, the maximum allowable response time, the distance from the accident coordinates to the material storage point, and the estimated transportation time of the materials from the material storage point to the accident coordinates. Based on the environmental risk index and the resource response capability index, a multi-objective route optimization model is constructed to obtain comprehensive decision indicators; Dynamic route planning is performed based on the environmental risk index, the resource response capability index, and the comprehensive decision-making index to obtain the route optimization coefficient. This includes: obtaining the environmental risk index of each transit point in the route; obtaining the time decay coefficient, which characterizes the degree of decay of the resource response capability index over time; and performing dynamic route planning based on the environmental risk index, the resource response capability index, the comprehensive decision-making index, and the time decay coefficient to determine the route optimization coefficient. Based on the environmental risk index, the resource response capability index, the comprehensive decision index, and the path optimization coefficient, the final decision index is calculated, and emergency response decisions are executed based on the final decision index.

2. The ship oil spill emergency response decision-making method based on multi-source data fusion according to claim 1, characterized in that, The environmental risk index is expressed as: ； in, It is a comprehensive environmental risk index. It is the wave height at time t. It is the wind speed at time t. It is the air pressure at time t. It is the visibility at time t. It is the water flow velocity at time t. It is the precipitation at time t. Coordinates Ship density in the area Coordinates The waterway congestion level in the area These are the first weight, the second weight, and the third weight, respectively.

3. The ship oil spill emergency response decision-making method based on multi-source data fusion according to claim 2, characterized in that, The resource response capability index is expressed as: ； in, It is a resource responsiveness index. It is the reserve quantity of the i-th material reserve point. This is the state of the j-th means of transport. The accident coordinates The straight-line distance to the material storage point. This is the estimated transportation time for supplies from the storage point to the accident coordinates (x, y). This is the maximum allowed response time. It is the fourth weight. It is the fifth weight.

4. The ship oil spill emergency response decision-making method based on multi-source data fusion according to claim 3, characterized in that, The comprehensive decision-making index, obtained by constructing a multi-objective route optimization model based on the environmental risk index and the resource response capability index, includes: Obtain baseline route length and standard fuel consumption; Obtain the actual route length from the accident coordinates to the material storage point, and the actual fuel consumption of the transport vehicle within the actual route length; Based on the environmental risk index, the resource response capability index, the baseline route length, the standard fuel consumption, the actual route length, and the actual fuel consumption, the multi-objective route optimization model is constructed, and the comprehensive decision index is determined based on the multi-objective route optimization model.

5. The ship oil spill emergency response decision-making method based on multi-source data fusion according to claim 4, characterized in that, The calculation of the final decision index based on the environmental risk index, the resource response capability index, the comprehensive decision index, and the path optimization coefficient includes: Obtain the maximum allowed response time; The comprehensive decision-making index is adjusted based on the maximum allowable response time to obtain the adjusted comprehensive decision-making index; The final decision index is calculated based on the environmental risk index, the resource response capability index, the adjusted comprehensive decision index, and the path optimization coefficient.

6. The ship oil spill emergency response decision-making method based on multi-source data fusion according to claim 5, characterized in that, The method further includes: When the final decision indicator is greater than the first threshold, the emergency response decision corresponding to the final decision indicator is executed immediately. When the final decision indicator is less than or equal to the first threshold and the final decision indicator is greater than or equal to the second threshold, the emergency response decision corresponding to the final decision indicator is adjusted to obtain an adjustment decision, and then the adjustment decision is executed. When the final decision indicator is less than the second threshold, the emergency response decision corresponding to the final decision indicator is discarded, and a new decision is made for the ship oil spill.

7. A ship oil spill emergency response decision-making system based on multi-source data fusion, characterized in that, The system includes: The data processing module is used to collect multi-source data related to ship oil spill emergency response decision-making, and to preprocess the multi-source data to obtain preprocessed multi-source data; the multi-source data includes real-time sea state data, meteorological data, maritime traffic data, and emergency resource data; The environmental risk module is used to calculate the environmental risk index of the sea area where the ship oil spill occurred based on the preprocessed multi-source data. It is also used to: extract wave height, wind speed, air pressure, visibility, water flow speed, and precipitation at a preset time from the multi-source data; obtain the ship density and channel congestion of the area where the preset coordinate point is located within the sea area where the ship oil spill occurred; and determine the environmental risk index based on the wave height, wind speed, air pressure, visibility, water flow speed, and precipitation at the preset time in the sea area where the ship oil spill occurred, as well as the ship density and channel congestion of the area where the preset coordinate point is located. The response capability module is used to assess emergency resource allocation capabilities based on the environmental risk index to obtain a resource response capability index. It is also used to: acquire the coordinates of the oil spill accident, the material storage point where the materials are located, and the maximum permissible response time for making emergency response decisions; determine the straight-line distance from the accident coordinates to the material storage point; determine the estimated transportation time of the materials from the material storage point to the accident coordinates; acquire the status of each means of transport and the reserve quantity at each material storage point; and determine the resource response capability index based on the status of each means of transport, the reserve quantity at each material storage point, the environmental risk index, the maximum permissible response time, the distance from the accident coordinates to the material storage point, and the estimated transportation time of the materials from the material storage point to the accident coordinates. The decision index module is used to construct a multi-objective route optimization model based on the environmental risk index and the resource response capability index to obtain comprehensive decision indexes; The route optimization module is used to perform dynamic route planning based on the environmental risk index, the resource responsiveness index, and the comprehensive decision-making index to obtain the route optimization coefficient. It is also used to: obtain the environmental risk index of each transit point in the route; obtain the time decay coefficient, which characterizes the degree of decay of the resource responsiveness index over time; and perform dynamic route planning based on the environmental risk index, the resource responsiveness index, the comprehensive decision-making index, and the time decay coefficient to determine the route optimization coefficient. The response decision module is used to calculate the final decision index based on the environmental risk index, the resource response capability index, the comprehensive decision index and the path optimization coefficient, and to execute emergency response decisions based on the final decision index.

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