Ship oil spill emergency response decision-making method and system based on multi-source data fusion

Abstract

The invention relates to a ship oil spill emergency response decision method and system based on multi-source data fusion, and the method comprises the steps: collecting multi-source data related to a ship oil spill emergency response decision, and carrying out the preprocessing of the multi-source data, and obtaining the preprocessed multi-source data; based on the preprocessed multi-source data, calculating an environmental risk index of a ship oil spill occurrence sea area; evaluating the emergency resource allocation capability based on the environmental risk index to obtain a resource response capability index; based on the environmental risk index and the resource response capability index, constructing a multi-target route optimization model 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 a path optimization coefficient; and calculating a final decision index based on the environmental risk index, the resource response capability index, the comprehensive decision index and the path optimization coefficient, and executing an emergency response decision. According to the invention, the accuracy and efficiency of ship oil spill emergency response decision can be improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a ship oil spill emergency response decision-making method, system, electronic equipment and non-transient computer-readable storage medium based on multi-source data fusion. Background Art

[0002] Nowadays, with the development of economic globalization, the scale of maritime transportation continues to expand, and transportation safety issues are becoming increasingly prominent, especially the increasing incidence of oil spill accidents. After an oil spill accident, pollution control materials are usually stored in coastal docks or designated warehouses. Once an accident occurs, the relevant emergency departments will quickly deploy pollution control materials to the accident area through ground or sea transportation according to the specific location of the accident. Existing emergency response measures usually rely on pre-planned emergency material deployment routes, and transport materials through manual operation or simple scheduling systems. Route selection mainly considers distance and time, and basically adopts preset waterways and conventional traffic information, striving to complete the transportation of materials in the shortest time.

[0003] However, since oil spills usually occur in vast and uncertain sea areas, the location of the accident is often difficult to predict, and oil spills may occur in multiple locations at the same time, it is difficult to meet the requirements for the timeliness and adequacy of material deployment. In addition, traditional methods only rely on a single data source, such as route information and transportation time, and fail to fully consider multiple complex factors such as real-time sea conditions, weather changes, and maritime traffic flow. As a result, in actual operations, route selection may not be optimal, delaying the efficiency of emergency response. Summary of the invention

[0004] In view of the technical problems existing in the prior art, the present invention provides a ship oil spill emergency response decision-making method, system, electronic device and non-transitory computer-readable storage medium 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 technical problems is as follows: The present invention provides a ship oil spill emergency response decision method based on multi-source data fusion, the method comprising: 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; the multi-source data includes real-time sea condition data, meteorological data, marine traffic data and emergency resource data; Based on the pre-processed multi-source data, calculating the environmental risk index of the sea area where the ship oil spill occurs; Evaluate the emergency resource deployment capability based on the environmental risk index to obtain a resource response capability index; Based on the environmental risk index and the resource response capacity index, a multi-objective route optimization model is constructed to obtain a comprehensive decision-making index; Perform dynamic path planning based on the environmental risk index, the resource response capability index and the comprehensive decision-making index to obtain a path optimization coefficient; Based on the environmental risk index, the resource response capability index, the comprehensive decision index and the path optimization coefficient, a final decision index is calculated, and an emergency response decision is executed based on the final decision index.

[0006] Optionally, the calculating the environmental risk index of the sea area where the ship oil spill occurs based on the preprocessed multi-source data includes: Extracting the wave height, wind speed, air pressure, visibility, water flow speed and precipitation at a preset time in the sea area where the ship oil spill occurs from the multi-source data; Obtain the ship density and channel congestion in the area where the preset coordinate point is located in the sea area where the ship oil spill occurs; 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 occurs at a preset time, as well as the ship density and channel congestion in the area where the preset coordinate point is located.

[0007] Optionally, the environmental risk index is expressed as: ; in, is a comprehensive environmental risk index. is the wave height at time t, is the wind speed at time t, is the air pressure at time t, is the visibility at time t, is the water velocity at time t, is the precipitation at time t, is the coordinate point The density of ships in the area, is the coordinate point The degree of waterway congestion in the area. They are the first weight, the second weight and the third weight respectively.

[0008] Optionally, the evaluating the emergency resource deployment capability based on the environmental risk index to obtain a resource response capability index includes: Obtain the coordinates of the accident point where the ship oil spill occurred, the material storage point where the materials are located, and the maximum allowable response time for making emergency response decisions; Determine the straight-line distance from the accident coordinate point to the material storage point; Determine the estimated transportation time of the materials from the accident coordinate point to the materials storage point; Obtaining the status of each means of transport and the reserve quantity of each of the material reserve points; The resource response capability index is determined based on the status of each of the transportation tools, the reserve quantity of each of the material storage points, the environmental risk index, the maximum allowable response time, the distance from the accident coordinate point to the material storage point, and the estimated transportation time of the materials from the accident coordinate point to the material storage point.

[0009] Optionally, the resource responsiveness index is expressed as: ; in, is the resource responsiveness index, is the reserve amount of the i-th material storage point, is the state of the j-th transport vehicle, The accident coordinate point The straight-line distance to the material storage point, is the estimated transportation time of materials from the accident coordinate point (x, y) to the material storage point, is the maximum allowed response time, is the fourth weight, It is the fifth weight.

[0010] Optionally, based on the environmental risk index and the resource response capability index, constructing a multi-objective route optimization model to obtain a comprehensive decision-making index includes: Obtain benchmark route length and standard fuel consumption; Obtaining the actual route length from the accident coordinate point to the material storage point, and the actual fuel consumption of the transportation tool in the actual route length; Based on the environmental risk index, the resource responsiveness index, the benchmark 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-making index is determined based on the multi-objective route optimization model.

[0011] Optionally, the dynamic path planning is performed based on the environmental risk index, the resource response capability index and the comprehensive decision-making index to obtain a path optimization coefficient, including: Obtain the environmental risk index of each transit point in the route; Obtaining a time decay coefficient representing the degree to which the resource response capability index decays over time; 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.

[0012] Optionally, the calculating 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: Obtaining the maximum allowed response time; Adjusting the comprehensive decision indicator based on the maximum allowed response time to obtain an adjusted comprehensive decision indicator; 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.

[0013] Optionally, the method further includes: When it is greater than the first threshold, the emergency response decision corresponding to the final decision indicator is immediately executed; When it is less than or equal to the first threshold and greater than or equal to the second threshold, adjusting the emergency response decision corresponding to the final decision indicator to obtain an adjusted decision, and executing the adjusted decision; When it is less than the second threshold, the emergency response decision corresponding to the final decision indicator is discarded, and a new decision on ship oil spill is made.

[0014] The present invention also provides a ship oil spill emergency response decision system based on multi-source data fusion, the system comprising: A data processing module is used to collect multi-source data related to ship oil spill emergency response decision-making, and pre-process the multi-source data to obtain pre-processed multi-source data; the multi-source data includes real-time sea condition data, meteorological data, marine traffic data and emergency resource data; An environmental risk module, used to calculate the environmental risk index of the sea area where the ship oil spill occurs based on the pre-processed multi-source data; A response capability module, used to evaluate the emergency resource deployment capability based on the environmental risk index to obtain a resource response capability index; A decision indicator module, used to construct a multi-objective route optimization model based on the environmental risk index and the resource response capability index to obtain a comprehensive decision indicator; A path optimization module, 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 a path 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 the emergency response decision based on the final decision index.

[0015] In addition, to achieve the above-mentioned purpose, the present invention also proposes an electronic device, comprising: a memory for storing a computer software program; a processor for reading and executing the computer software program, thereby realizing a ship oil spill emergency response decision-making method based on multi-source data fusion as described above.

[0016] In addition, to achieve the above-mentioned purpose, the present invention also proposes a non-transitory computer-readable storage medium, in which a computer software program is stored. When the computer software program is executed by a processor, a ship oil spill emergency response decision-making method based on multi-source data fusion as described above is implemented.

[0017] The beneficial effects of the present invention are: (1) The present invention adopts a decision-making method based on multi-source data fusion, which effectively improves the accuracy of decision-making by comprehensively considering sea data, meteorological data, maritime traffic conditions and real-time information of emergency resources. 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 avoid decision-making errors caused by insufficient or biased information. (2) The present invention introduces the Environmental Risk Assessment Index (ERI) to comprehensively assess the potential impact of changes in marine environmental conditions (such as wave height, wind speed, current, 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.

[0018] (3) The present invention evaluates the emergency resource allocation capability by designing a resource response capability index (RCI) that comprehensively considers factors such as the amount of material reserves, the status of transportation tools, and the time of resource arrival. This evaluation can ensure that emergency resources can be allocated quickly and efficiently under limited resources, improve emergency response efficiency, and reduce delays caused by resource shortages or improper allocation.

[0019] In summary, the present invention achieves scientific decision-making and optimization of emergency response to ship oil spills by introducing a series of innovative measures such as multi-source data fusion, environmental risk assessment, resource allocation optimization, route planning and dynamic adjustment. Its beneficial effects are not only reflected in improving decision-making accuracy, optimizing resource utilization and reducing costs, but also in strengthening the timeliness, flexibility and sustainability of emergency response, so that emergency response to oil spill accidents can be carried out more efficiently, safely and environmentally friendly. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A flowchart of a ship oil spill emergency response decision method based on multi-source data fusion provided by the present invention; Figure 2A 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; Figure 3 A schematic diagram of the hardware structure of a possible electronic device provided by the present invention; Figure 4 A schematic diagram of the hardware structure of a possible computer-readable storage medium provided by the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0022] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0023] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or description". Any embodiment described as "for example" in the present invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any technician in the field to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present invention.

[0024] See also Figure 1 , provides a flow chart of a ship oil spill emergency response decision method based on multi-source data fusion of the present invention, comprising the following steps: Step 201: collect multi-source data related to ship oil spill emergency response decision-making, and pre-process the multi-source data to obtain pre-processed multi-source data.

[0025] Among them, multi-source data can include real-time sea condition data, meteorological data, maritime traffic data and emergency resource data.

[0026] Specifically, the collection and preprocessing of multi-source data is an important step to ensure the scientificity and accuracy of emergency response decisions. By collecting and processing different types of data in real time, it can provide a high-quality information basis for subsequent environmental risk assessment, resource allocation optimization, path planning and other decisions. The preprocessing of multi-source data is the key to improving data quality, aiming to eliminate noise, standardize data formats and ensure that data can be used for subsequent analysis and decision-making.

[0027] Real-time sea state data is key data for describing the marine environment, usually including variables such as wave height, wind speed, and water flow speed. These data can reflect the dynamic conditions on the sea surface, and have an important impact on the spread of oil spill accidents, the difficulty and safety of emergency response. Sea state data can be obtained in real time through marine monitoring equipment (such as buoys, satellite remote sensing, ship-borne sensors, etc.). These devices can obtain real-time data on dynamic changes in waves, wind speed, water flow, etc. Sea state data directly affects the speed and range of oil spill spread. The greater the wave height, wind speed, and water flow speed, the greater the speed and range of oil pollution spread, and the greater the difficulty of emergency response.

[0028] Meteorological data includes variables such as visibility, precipitation, and air pressure, which describe the atmospheric conditions in the marine environment. Meteorological conditions are an important factor in oil spill emergency response, affecting the navigation of ships, the visibility of rescue operations, the speed of oil spill spread, etc. Meteorological data can be obtained through meteorological 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, precipitation, etc.) will increase the difficulty of emergency response, affect 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.

[0029] Maritime traffic data includes information such as ship density and waterway congestion, which reflects the flow and busyness of maritime traffic. This type of data can help assess the activities of ships near the 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, marine monitoring system, etc. These systems can provide data on the location, speed, navigation track and density of ships. Ship density and waterway congestion affect the dispatch of emergency resources. Dense ship traffic and congested waterways will increase the complexity of emergency response, making resource allocation and route planning more difficult.

[0030] Emergency resource data refers to information such as the amount of material reserves, the status of transportation vehicles, and staffing required for oil spill emergency response. It includes the status and distribution of oil adsorbent materials, rescue equipment, and transport vessels. Emergency resource data is usually 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 affects the speed and efficiency of response. When resources are sufficient and transportation vehicles are in good condition, emergency response can be carried out quickly. On the contrary, resource shortages or poor transportation vehicle conditions will delay response time and even affect the safety of rescue operations.

[0031] In some embodiments, the goal of preprocessing multi-source data is to convert different types of data into a unified format and perform steps such as denoising, filling missing values, and standardization to ensure data quality and usability for subsequent analysis.

[0032] In summary, by collecting and preprocessing multi-source data (such as sea condition data, meteorological data, maritime traffic data and emergency resource data), the present invention can provide comprehensive and accurate information support for oil spill emergency response. The preprocessing process includes steps such as data cleaning, format standardization, fusion, and deduplication to ensure data quality and processing efficiency. Through high-quality multi-source data input, it can provide a solid data foundation for environmental risk assessment, resource allocation, path optimization and other decision-making, thereby ensuring the efficiency and scientificity of emergency response.

[0033] Step 202: Calculate the environmental risk index of the sea area where the ship oil spill occurs based on the pre-processed multi-source data.

[0034] In some embodiments, step 202 may include: Extracting the wave height, wind speed, air pressure, visibility, water flow speed and precipitation at a preset time in the sea area where the ship oil spill occurs from the multi-source data; Obtain the ship density and channel congestion in the area where the preset coordinates of the ship oil spill occurred; 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 occurs at a preset time, as well as the ship density and channel congestion in the area where the preset coordinate point is located.

[0035] In some embodiments, the environmental risk index may be expressed as: ; in, is a comprehensive environmental risk index. is the wave height at time t, is the wind speed at time t, is the air pressure at time t, is the visibility at time t, is the water velocity at time t, is the precipitation at time t, is the coordinate point The density of ships in the area, is the coordinate point The degree of waterway congestion in the area. They are the first weight, the second weight and the third weight respectively.

[0036] In the specific implementation, Wave height reflects the fluctuation of the sea surface and is an important factor affecting the speed of oil spill spread and the difficulty of cleanup. The greater the wave height, the worse the sea conditions, the wider the oil spill may spread, and the greater the difficulty of emergency response.

[0037] Wind speed is another important factor affecting the spread of oil spills. The higher the wind speed, the faster the oil will be blown away and the wider the spread will be.

[0038] and These two parameters play a limiting role. 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 lower the efficiency of search and rescue and emergency resource dispatch, which increases the complexity of response.

[0039] This part of the formula calculates the relationship between wave height, wind speed, air pressure, and visibility, and uses the weight coefficient Adjustments are made to reflect the impact of these climate factors on the environmental risks of oil spills. This impact is mainly reflected in changes in marine climate, especially in severe weather conditions, where sea surface conditions and visibility have a direct impact on the difficulty and efficiency of emergency response.

[0040] The speed of water flow directly affects the speed at which oil pollution spreads on the water surface. The faster the water flow, the faster the oil pollution spreads, and the wider the risk range is.

[0041] The amount of precipitation affects the dilution and dissolution of oil on the sea surface. When there is heavy precipitation, the oil on the water surface may be diluted and mixed with the water, affecting the cleanup of the oil spill.

[0042] This part expresses the influence of fluidity factors in the environment by multiplying the water velocity and precipitation. The square operation emphasizes the nonlinear effect of water flow and precipitation on the spread of oil spills. Due to the large changes in water flow and precipitation, the weight coefficient is used. and higher-order equations to emphasize their risk impact on emergency response decisions.

[0043] is the coordinate point The ship density in the area reflects the concentration of ships in a certain navigation area. Too high a density will increase the risk of collision or traffic accidents between ships and may hinder the rapid entry and operation of emergency response teams.

[0044] The degree of waterway congestion is an indicator to measure the waterway's navigable capacity. When the congestion is severe, it will cause the movement of ships to be slow, affecting the efficiency of the deployment of resources and personnel in oil spill accidents.

[0045] This is done by calculating the ratio of ship density to channel congestion and weighting it using an exponential function. Risk increases dramatically when ship density is high and the channel is congested, as these factors limit the timeliness and effectiveness of emergency response. The weights are adjusted, and the nonlinear impact of ship density and congestion on environmental risks is strengthened through an exponential relationship.

[0046] Each weight controls the relative importance of each factor in the comprehensive environmental risk assessment. By adjusting these coefficients, the impact of each factor can be flexibly adjusted according to specific environmental conditions. Controlling the contribution of wave height and wind speed to environmental risks, Controlling the contribution of water flow and precipitation to risk, Control the contribution of ship density and channel congestion to risk. The sum of the three weights equals 1, ensuring that the sum of the weights of the entire assessment formula is 1, so that the risk assessment remains balanced among all factors.

[0047] ERI comprehensively considers the multi-factor environmental risk indicators of marine meteorological conditions, ocean mobility, traffic conditions and ship activities. The higher the ERI value, the greater the risk and the greater the difficulty of emergency response. ERI provides a scientific basis for emergency response decisions. It helps decision makers identify the most dangerous sea conditions and provides a reference for resource scheduling, path planning and task execution. By calculating ERI, the environmental complexity of oil spill accidents can be quickly assessed, so as to formulate response strategies.

[0048] In summary, the environmental risk assessment index (ERI) of the present invention provides a numerical indicator that can dynamically reflect the correlation between the current environmental conditions and the oil spill emergency response through comprehensive calculation of multiple environmental factors. Through weighted calculation of key factors such as wave height, wind speed, air pressure, visibility, water flow speed, precipitation, ship density and waterway congestion, ERI can effectively assess the current environmental risks and provide theoretical support for emergency response decisions.

[0049] Step 203: Evaluate the emergency resource allocation capability based on the environmental risk index to obtain a resource response capability index.

[0050] In some embodiments, step 203 may include: Obtain the coordinates of the accident point where the ship oil spill occurred, the material storage point where the materials are located, and the maximum allowable response time for making emergency response decisions; Determine the straight-line distance from the accident coordinate point to the material storage point; Determine the estimated transportation time of the materials from the accident coordinate point to the materials storage point; Obtaining the status of each means of transport and the reserve quantity of each of the material reserve points; The resource response capability index is determined based on the status of each of the transportation tools, the reserve quantity of each of the material storage points, the environmental risk index, the maximum allowable response time, the distance from the accident coordinate point to the material storage point, and the estimated transportation time of the materials from the accident coordinate point to the material storage point.

[0051] In some embodiments, the resource responsiveness index may be expressed as: ; in, is the resource responsiveness index, is the reserve amount of the i-th material storage point, is the state of the j-th transport vehicle, The accident coordinate point The straight-line distance to the material storage point, is the estimated transportation time of materials from the accident coordinate point (x, y) to the material storage point, is the maximum allowed response time, is the fourth weight, It is the fifth weight.

[0052] In the specific implementation, Indicates the amount of reserves at different material storage points. Here i represents the index of the material storage point (e.g. oil adsorbent material, emergency equipment, etc.). The larger the material reserves, the more resources can be provided in an oil spill incident, thereby improving the response capability.

[0053] is the status of the transport. Here j is the index of the transport (e.g., emergency ship, transport vehicle, etc.). If the transport is in good condition and has a strong carrying capacity, it can deliver emergency supplies more quickly. Therefore, A larger value indicates that resources can be deployed and delivered quickly.

[0054] This part reflects the direct relationship between material reserves and transportation tools. The amount of material reserves and the status of transportation tools directly determine the potential for emergency response. Through product operations, the coordination ability of material reserves and transportation tools can be quantified.

[0055] Indicates the accident coordinate point The straight-line distance to the material storage point. The shorter the straight-line distance, the lower the time cost of material deployment and transportation, and the faster the response speed. Conversely, when the distance is longer, the time and resources required for transportation will increase, and the efficiency of emergency response will decrease.

[0056] ERI is the Environmental Risk Assessment Index, which reflects the complexity and difficulty of emergency response caused by the current marine environmental conditions. The higher the ERI value, the greater the environmental risk and the greater the difficulty of response. Therefore, distant material storage points and areas with higher environmental risks will increase the complexity of response accordingly.

[0057] This part takes distance and environmental risks into consideration and weights the distance from the material storage point to the accident site and the impact of environmental complexity. Long distances or high environmental risks will significantly increase the difficulty and time required for emergency response. Therefore, this part reflects the negative impact of distance and environmental risks on resource allocation efficiency in a weighted manner.

[0058] Indicates the coordinate point of the accident Estimated transportation time to the material storage point. Long estimated transportation time means delayed emergency response, affecting the timeliness of accident handling. Indicates the maximum allowable response time, that is, the upper limit of the emergency response time. If the response exceeds this limit, it will be considered invalid or unqualified. Therefore, the control of transportation time is crucial to improve responsiveness.

[0059] The impact of transportation time is attenuated. The closer the response time is to the maximum allowable response time, the smaller the index value is, resulting in a decrease in the RCI value; conversely, when the response time is shorter, the index value is larger and the RCI value is higher. This part reflects the impact of transportation time on emergency response capabilities. If the estimated transportation time is too long and exceeds the maximum allowable response time, the exponential attenuation causes the RCI value to drop rapidly, indicating that the resource response capacity is significantly reduced and decision makers need to adjust the emergency plan.

[0060] is the fourth weight, It is the fifth weight, which adjusts the relative importance of material reserves and transportation status in RCI. , which can emphasize or weaken the impact of the status of resource reserves and transportation tools on emergency response capabilities. You can adjust the importance of shipping time in RCI. The value indicates that the impact of transportation time on response capacity is considered to be more important. By adjusting the parameters of model flexibility, the contribution ratio of different factors in RCI can be adjusted according to actual needs, thereby reflecting the priority factors of emergency response in different scenarios.

[0061] RCI is a comprehensive index used to measure the overall resource allocation capability and efficiency of the emergency response system. The higher the RCI value, the stronger the emergency resource allocation capability in terms of material reserves, transportation tool scheduling, etc., and the faster and more effective response to oil spills. Through the calculation of RCI, decision makers can evaluate the current resource response capability and determine whether it is necessary to further optimize resource allocation, transportation tool scheduling or response strategy. If the RCI value is low, it may be necessary to optimize the location of material storage points, increase the availability of transportation tools, or shorten transportation time.

[0062] In summary, the RCI (Resource Response Capacity Index) of the present invention quantifies the deployment capacity of emergency response resources by comprehensively evaluating factors such as material reserves, transportation tool status, distance, environmental risks and transportation time. The index is designed to help decision makers identify and optimize resource allocation, ensuring that resources can be quickly and effectively deployed during the oil spill emergency response process, thereby improving the efficiency and timeliness of emergency response.

[0063] Step 204: Based on the environmental risk index and the resource response capability index, a multi-objective route optimization model is constructed to obtain a comprehensive decision-making index.

[0064] In some embodiments, step 204 may include: Obtain benchmark route length and standard fuel consumption; Obtaining the actual route length from the accident coordinate point to the material storage point, and the actual fuel consumption of the transportation tool in the actual route length; Based on the environmental risk index, the resource responsiveness index, the benchmark 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-making index is determined based on the multi-objective route optimization model.

[0065] In some embodiments, the comprehensive decision indicator can be expressed as: ; in, is a comprehensive decision-making indicator. The accident coordinate point The actual route length to the material storage point, is the baseline route length, is the standard fuel consumption, is the actual fuel consumption, is the sixth weight, is the seventh weight, It is the eighth weight.

[0066] In specific implementation, RCI is an indicator for evaluating the emergency resource allocation capability. The higher the RCI value, the stronger the response capability of material reserves and transportation tools, and the faster resources can be dispatched for emergency response.

[0067] ERI measures the impact of current environmental conditions on emergency response. The higher the ERI value, the greater the environmental risk, resulting in a more difficult emergency response.

[0068] Control the influence of RCI and ERI on the comprehensive decision-making index. The weights of resource responsiveness and environmental risk on path selection are determined. A high value means that more attention is paid to resource responsiveness and environmental risks, and more attention will be paid to the balance of these two factors during optimization.

[0069] This part comprehensively considers the impact of resource response capacity and environmental risks through a weighted combination of RCI and ERI. The negative impact of environmental risks is converted from 0 to 1, so that when environmental risks increase, the optimization goal is more inclined to choose a path that can reduce environmental risks.

[0070] Indicates the coordinate point of the accident The actual route length to the material storage point. The longer the actual route length, the longer the transportation distance, the more time and resources required. is the length of the reference route, usually the shortest path from the accident point to the target point. This length is a standard value and represents the length of the optimal route. The importance of controlling route length in comprehensive decision making. A larger value means that more attention is paid to path length, and shorter routes will be preferred during optimization.

[0071] This part measures the impact of route length on emergency response efficiency by calculating the ratio of actual route length to benchmark route length. When the actual route length is longer, it means that the transportation time and resource consumption are higher, thus the contribution to the comprehensive decision-making index is lower. In the optimization process, shorter routes will be chosen to save resources.

[0072] It is the standard fuel consumption, usually the expected fuel consumption under standard sailing conditions. It represents the amount of fuel required for sailing under ideal conditions. It is the actual fuel consumption, which indicates the amount of fuel consumed in actual navigation, depending on environmental conditions and route selection. The influence of controlling fuel consumption on comprehensive decision-making indicators. A higher value indicates more concern about fuel consumption, and optimization tends to reduce fuel consumption.

[0073] This section measures the impact of route optimization on fuel use by calculating the ratio of standard fuel consumption to actual fuel consumption. The lower the fuel consumption, the more optimized the route selection is, which can reduce the cost of emergency response. If the actual fuel consumption is close to the standard value, it means that the route selection efficiency is high and the optimization effect is good.

[0074] The entire expression is integrated to represent the cumulative impact of each decision factor over a certain time frame (perhaps the entire emergency response process). The integration operation allows the impact of time changes on each decision factor to be considered during the optimization process, so that the decision can dynamically adapt to changes in the emergency environment. Through integration, the impact of various factors that change over time during the emergency response process can be captured, making the decision more dynamic and adaptable to real-time changing environmental conditions.

[0075] CDI is a comprehensive decision-making indicator that combines multiple aspects such as resource response capability, environmental risk, route length and fuel consumption, and reflects the efficiency of route selection and emergency response after comprehensive optimization. The higher the CDI value, the better the optimization plan. The path selected after comprehensively considering factors such as time, resources, and environment can both reduce risks and improve resource utilization efficiency. By calculating CDI, decision makers can choose the best path among multiple optional paths. CDI helps decision makers minimize time, cost and environmental risks while meeting emergency response needs, and achieve optimal allocation of emergency resources. The design of CDI takes into account multiple optimization objectives, such as resource response, time, route length, fuel consumption, etc. By adjusting the weighting coefficient, the priority of the optimization objectives can be flexibly adjusted according to different emergency scenarios to ensure that the emergency response plan is both efficient and economical.

[0076] In summary, the comprehensive decision index (CDI) of the present invention helps decision makers choose the optimal path by weighted combination of multiple factors (resource response capability, environmental risk, route length, fuel consumption, etc.). The design of CDI enables emergency response decisions to balance different goals, such as time, resources, cost and environmental risks, thereby providing a comprehensive and scientific decision-making basis for emergency response. In practical applications, CDI can dynamically adjust decisions, optimize emergency response processes, and improve response efficiency and resource utilization.

[0077] 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 a path optimization coefficient.

[0078] In some embodiments, step 205 may include: Obtain the environmental risk index of each transit point in the route; Obtaining a time decay coefficient representing the degree to which the resource response capability index decays over time; 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.

[0079] In some embodiments, the path optimization coefficient can be expressed as: ; in, is the path optimization coefficient, k is the time decay coefficient, is the environmental risk index of the i-th transfer point on the route, is the ninth weight, is the tenth weight, It is the eleventh weight.

[0080] In the specific implementation, CDI is a key indicator of multi-objective optimization, which integrates multiple factors such as the fuel consumption, path length, and resource response capability of the route. The higher the CDI value, the better the route is in terms of overall decision-making. RCI evaluates the ability to allocate emergency resources and reflects the effectiveness of resource allocation. The higher the RCI value, the stronger the resource allocation capability and the faster the response. The k time decay coefficient is used to control the degree of attenuation of the impact of RCI on path optimization over time. As time goes by, the impact of RCI on path selection gradually decreases, indicating that as the emergency response process progresses, the efficiency of resource allocation gradually becomes a secondary factor affecting route selection.

[0081] This part takes into account the decision-making efficiency and resource allocation capabilities of the route through a weighted combination of CDI and RCI. Adjustments are made to the impact of time so that path selection can be flexibly adjusted according to changes in resource allocation capabilities during route optimization.

[0082] Represents the environmental risk of the i-th transfer point on the route. The higher the ERI value, the greater the environmental risk of the point and the greater the impact on emergency response. The environmental risk of each transfer point is taken into account, especially the potential impact on the navigation safety of ships and the spread of oil spills. The product operation is used to combine the environmental risk index of each transfer point into one indicator, which represents the environmental risk of the entire route. The high environmental risk of each transfer point will lead to a decrease in the optimization index of the entire route, ultimately affecting the route selection.

[0083] This part reflects the impact of the environmental risk of each transfer point on the route on the overall route optimization through a product relationship. The higher the environmental risk of each transfer point, the worse the route optimization effect, and vice versa. The introduction of this item emphasizes the importance of environmental risk to route selection. In high-risk areas, the optimization of route selection will be more cautious.

[0084] It is the maximum allowable response time, that is, the latest time limit for emergency response. If the emergency response exceeds this time, the best emergency window may be missed, resulting in wider spread of oil spills and more serious pollution. The estimated transportation time from the accident site to the material storage site or other key points. The shorter the transportation time, the faster the emergency response and the better the path selection.

[0085] This section reflects the impact of transportation time on route selection. By using the ratio of maximum response time to actual transportation time, we ensure that the emergency response time does not exceed the set maximum response time. If the transportation time is too long, the POI value will drop significantly, forcing the optimization scheme to prioritize shorter routes, thereby ensuring that the emergency response is completed in the shortest time.

[0086] The ninth weight adjusts the influence of the comprehensive decision index (CDI) and the resource response capacity index (RCI) in route optimization. This weight controls the trade-off between decision 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. If the environmental risk is high, the weight of this item will increase, forcing the route selection to be more cautious. The eleventh weight adjusts the weight of transportation time in route optimization. This weight determines the relative importance of emergency response time in route selection, ensuring that emergency response is completed within the specified time as much as possible.

[0087] 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.

[0088] In some embodiments, step 206 may include: Obtaining the maximum allowed response time; Adjusting the comprehensive decision indicator based on the maximum allowed response time to obtain an adjusted comprehensive decision indicator; 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.

[0089] In some embodiments, the final decision metric can be expressed as: ; in, It is the final decision indicator. As an example only, assuming that the first threshold is 0.8 and the second threshold is 0.5, the plan will be executed immediately when FDI>0.8; when 0.5≤FDI≤0.8, the plan needs to be adjusted; when FDI<0.5, the plan will be re-formulated.

[0090] In specific implementation, executing the emergency response decision is the last step of the entire emergency response system. The key is to determine whether to immediately implement the emergency response plan or adjust and reformulate the plan based on the final decision index (FDI) calculated previously. The purpose of this stage is to ensure that the emergency response can be carried out efficiently and timely, and to minimize the environmental pollution and economic losses caused by the oil spill accident.

[0091] The process of executing emergency response decisions depends on the calculation of various indicators before, especially the parameters related to comprehensive decision-making (such as environmental risk index ERI, resource response capacity index RCI, comprehensive decision index CDI, etc.). Specifically, the final decision index (FDI) is the output of the entire decision chain. Depending on the FDI value, the decision maker will take different actions.

[0092] When FDI is greater than the first threshold of 0.8, it means that according to the calculation results of various factors such as current environmental risks, resource response capabilities, and path optimization, the current emergency response plan performs well in terms of efficiency, timeliness, and feasibility, and meets the conditions for rapid startup. In this case, the emergency response plan can be implemented immediately. Emergency resources will be mobilized quickly, and ships, rescue teams, and cleanup equipment will enter the accident site as soon as possible to clean up and control the oil spill. The goal is to control the spread of oil pollution in the shortest time and reduce further harm to the environment.

[0093] When FDI is between the first and second thresholds, for example, between 0.5 and 0.8, it means that although the current plan can be implemented, there is still room for optimization, and there may be some problems such as insufficient resource allocation, insufficient path optimization, and high environmental risks. This means that although the emergency response can be initiated, the effect may not be as expected, and dynamic adjustments may be required during the implementation process.

[0094] When FDI is less than the second threshold of 0.5, it means that there are major problems with the current emergency response plan, such as insufficient resource allocation, excessive environmental risks, or unreasonable path selection, which may lead to long response time or waste of resources, and ultimately fail to effectively control the oil spill accident. At this time, the implementation effect of the emergency response plan will be greatly reduced, and may even have a negative impact. In this case, the plan should be re-formulated immediately. It may be necessary to re-evaluate the resource situation, adjust the response strategy, and even change the key decisions of the emergency response, such as selecting a new route, reallocating emergency resources, or designing a new plan based on new environmental changes. The re-formulation of the plan may also include adjusting the maximum response time or improving the environmental risk assessment (ERI).

[0095] The core of the emergency response decision-making of the present invention is to judge the feasibility and timeliness of the emergency response plan through FDI (Final Decision Index), and decide whether to immediately implement the plan, adjust the plan or re-formulate the plan according to the value of FDI. Through the comprehensive evaluation of environmental risks, resource response capabilities, path optimization and comprehensive decision-making, it ensures that the emergency response can be implemented efficiently, timely and accurately, and minimizes the environmental impact and economic losses caused by the accident.

[0096] See also Figure 2 , Figure 2 A structural schematic diagram of a ship oil spill emergency response decision system based on multi-source data fusion provided by the present invention.

[0097] like Figure 2 As shown, a ship oil spill emergency response decision system based on multi-source data fusion proposed in an embodiment of the present invention includes: The data processing module 301 is used to collect multi-source data related to ship oil spill emergency response decision-making, and pre-process the multi-source data to obtain pre-processed multi-source data; the multi-source data includes real-time sea state data, meteorological data, marine traffic data and emergency resource data; Environmental risk module 302, for calculating the environmental risk index of the sea area where the ship oil spill occurs based on the pre-processed multi-source data; A response capability module 303 is used to evaluate the emergency resource deployment capability based on the environmental risk index to obtain a resource response capability index; A decision indicator 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 a comprehensive decision indicator; A 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 a path optimization coefficient; 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 execute the emergency response decision based on the final decision index.

[0098] See also Figure 3 , Figure 3 Schematic diagram of an electronic device provided by an embodiment of the present invention. 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, the following steps are implemented: 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; the multi-source data includes real-time sea condition data, meteorological data, marine traffic data and emergency resource data; Based on the pre-processed multi-source data, calculating the environmental risk index of the sea area where the ship oil spill occurs; Evaluate the emergency resource deployment capability based on the environmental risk index to obtain a resource response capability index; Based on the environmental risk index and the resource response capacity index, a multi-objective route optimization model is constructed to obtain a comprehensive decision-making index; Perform dynamic path planning based on the environmental risk index, the resource response capability index and the comprehensive decision-making index to obtain a path optimization coefficient; Based on the environmental risk index, the resource response capability index, the comprehensive decision index and the path optimization coefficient, a final decision index is calculated, and an emergency response decision is executed based on the final decision index.

[0099] See also Figure 4 , Figure 4 A schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present invention. 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, the following steps are implemented: 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; the multi-source data includes real-time sea condition data, meteorological data, marine traffic data and emergency resource data; Based on the pre-processed multi-source data, calculating the environmental risk index of the sea area where the ship oil spill occurs; Evaluate the emergency resource deployment capability based on the environmental risk index to obtain a resource response capability index; Based on the environmental risk index and the resource response capacity index, a multi-objective route optimization model is constructed to obtain a comprehensive decision-making index; Perform dynamic path planning based on the environmental risk index, the resource response capability index and the comprehensive decision-making index to obtain a path optimization coefficient; Based on the environmental risk index, the resource response capability index, the comprehensive decision index and the path optimization coefficient, a final decision index is calculated, and an emergency response decision is executed based on the final decision index.

[0100] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0101] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented 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.

[0102] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A system that specifies the functions of a box or multiple boxes.

[0103] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction system, which is implemented in the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0104] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0105] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0106] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A ship oil spill emergency response decision method based on multi-source data fusion, characterized in that: The method comprises: 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; the multi-source data includes real-time sea condition data, meteorological data, marine traffic data and emergency resource data; Based on the pre-processed multi-source data, calculating the environmental risk index of the sea area where the ship oil spill occurs; Evaluate the emergency resource deployment capability based on the environmental risk index to obtain a resource response capability index; Based on the environmental risk index and the resource response capacity index, a multi-objective route optimization model is constructed to obtain a comprehensive decision-making index; Perform dynamic path planning based on the environmental risk index, the resource response capability index and the comprehensive decision-making index to obtain a path optimization coefficient; Based on the environmental risk index, the resource response capability index, the comprehensive decision index and the path optimization coefficient, a final decision index is calculated, and an emergency response decision is 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 is characterized in that: The calculating of the environmental risk index of the sea area where the ship oil spill occurs based on the pre-processed multi-source data comprises: Extracting the wave height, wind speed, air pressure, visibility, water flow speed and precipitation at a preset time in the sea area where the ship oil spill occurs from the multi-source data; Obtain the ship density and channel congestion in the area where the preset coordinate point is located in the sea area where the ship oil spill occurs; 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 occurs at a preset time, as well as the ship density and channel congestion in the area where the preset coordinate point is located.

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

4. The ship oil spill emergency response decision-making method based on multi-source data fusion according to claim 3 is characterized in that: The step of evaluating the emergency resource deployment capability based on the environmental risk index to obtain a resource response capability index includes: Obtain the coordinates of the accident point where the ship oil spill occurred, the material storage point where the materials are located, and the maximum allowable response time for making emergency response decisions; Determine the straight-line distance from the accident coordinate point to the material storage point; Determine the estimated transportation time of the materials from the accident coordinate point to the materials storage point; Obtaining the status of each means of transport and the reserve quantity of each of the material reserve points; The resource response capability index is determined based on the status of each of the transportation tools, the reserve quantity of each of the material storage points, the environmental risk index, the maximum allowable response time, the distance from the accident coordinate point to the material storage point, and the estimated transportation time of the materials from the accident coordinate point to the material storage point.

5. The ship oil spill emergency response decision-making method based on multi-source data fusion according to claim 4 is characterized in that: The resource responsiveness index is expressed as: ； in, is the resource responsiveness index, is the reserve amount of the i-th material storage point, is the state of the j-th transport vehicle, The accident coordinate point The straight-line distance to the material storage point, is the estimated transportation time of materials from the accident coordinate point (x, y) to the material storage point, is the maximum allowed response time, is the fourth weight, It is the fifth weight.

6. The ship oil spill emergency response decision-making method based on multi-source data fusion according to claim 5 is characterized in that: The multi-objective route optimization model is constructed based on the environmental risk index and the resource response capability index to obtain a comprehensive decision-making index, including: Obtain benchmark route length and standard fuel consumption; Obtaining the actual route length from the accident coordinate point to the material storage point, and the actual fuel consumption of the transportation tool in the actual route length; Based on the environmental risk index, the resource responsiveness index, the benchmark 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-making index is determined based on the multi-objective route optimization model.

7. The ship oil spill emergency response decision-making method based on multi-source data fusion according to claim 6 is characterized in that: The 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, including: Obtain the environmental risk index of each transit point in the route; Obtaining a time decay coefficient representing the degree to which the resource response capability index decays over time; 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.

8. The ship oil spill emergency response decision-making method based on multi-source data fusion according to claim 7 is characterized in that: The calculating 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 comprises: Obtaining the maximum allowed response time; Adjusting the comprehensive decision indicator based on the maximum allowed response time to obtain an adjusted comprehensive decision indicator; 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.

9. The ship oil spill emergency response decision-making method based on multi-source data fusion according to claim 8 is characterized in that: The method further comprises: When it is greater than the first threshold, the emergency response decision corresponding to the final decision indicator is immediately executed; When it is less than or equal to the first threshold and greater than or equal to the second threshold, adjusting the emergency response decision corresponding to the final decision indicator to obtain an adjusted decision, and executing the adjusted decision; When it is less than the second threshold, the emergency response decision corresponding to the final decision indicator is discarded, and a new decision on ship oil spill is made.

10. A ship oil spill emergency response decision system based on multi-source data fusion, characterized in that: The system comprises: A data processing module is used to collect multi-source data related to ship oil spill emergency response decision-making, and pre-process the multi-source data to obtain pre-processed multi-source data; the multi-source data includes real-time sea condition data, meteorological data, marine traffic data and emergency resource data; An environmental risk module, used to calculate the environmental risk index of the sea area where the ship oil spill occurs based on the pre-processed multi-source data; A response capability module, used to evaluate the emergency resource deployment capability based on the environmental risk index to obtain a resource response capability index; A decision indicator module, used to construct a multi-objective route optimization model based on the environmental risk index and the resource response capability index to obtain a comprehensive decision indicator; A path optimization module, 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 a path 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 the emergency response decision based on the final decision index.

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