84 results about "Ship routing" patented technology

The invention discloses an offshore platform anti-collision device and method based on multi-mode BEV perception, and the device comprises a three-dimensional fusion distance measurement module, a UWB distance measurement module, a ship navigation state monitoring module, a platform marine environment monitoring module, and a central processing unit. The three-dimensional fusion ranging module comprises a holder, a laser radar and a camera, and is used for performing 360-degree three-dimensional scanning on the periphery of the offshore platform; the UWB distance measuring modules are installed on the periphery of a ship and pile legs of an offshore platform. The ship navigation state monitoring module is used for acquiring ship position, navigational speed and course information in real time; the platform marine environment monitoring module collects wind wave data and weather data near the offshore platform and route information of passing ships through network communication. The invention discloses an offshore platform anti-collision device with real-time monitoring and collision risk assessment functions, the anti-collision safety of an offshore platform is improved, and the occurrence rate of collision accidents is reduced.

The invention discloses a ship path planning method and system based on Beidou grid codes, and belongs to the technical field of path planning, and the method comprises the steps: obtaining planning data of a to-be-planned area of a ship, carrying out the priority level division of the ship, and combining a prior path, a priority level and a planning index, a grid chart based on Beidou grid codes is generated through a real environment Beidou grid code management module to perform global path planning, collision risk analysis is performed according to real-time sensing data of a navigation positioning system, an AIS, an electric gyrocompass, a log, waves and weather forecast, a path planning effect is evaluated according to task completion efficiency after planning, and the path planning efficiency is improved. According to the method, real-time sensing data such as port information, ship route information, route planning historical data and meteorological information of ships are analyzed and excavated, the route is recommended, the safety, economical efficiency and reliability of the route are improved, and the method is suitable for large-scale popularization and application. And the intelligent level and the operation efficiency of the ship are improved.

The invention discloses a marine transportation supply chain risk identification and early warning method based on a dynamic knowledge graph, and the method comprises the steps: carrying out the entity identification of multi-source data according to a global ontology model, so as to obtain the structural data of a marine transportation supply chain; obtaining a dynamic knowledge graph according to the sea transportation supply chain structured data; performing risk conduction path analysis on the marine transportation supply chain based on the dynamic knowledge graph to obtain a risk event cascade effect value of the marine transportation supply chain; on the basis of the constructed risk probability prediction model, predicting and outputting a path comprehensive identification risk value of the ship route according to the dynamic knowledge graph in combination with the risk event cascade effect value; and according to the path comprehensive identification risk value, dividing an early warning level, and according to the early warning level, realizing early warning and decision-making of the marine transportation supply chain. According to the method, the problems of global view missing, insufficient risk relevance insight, prediction lag and the like caused by data islands in an existing method are solved, and the problems of poor real-time performance and accuracy of risk management of the marine transportation supply chain are solved.

The invention discloses a ship route optimization and safety management method based on real-time environment information, and relates to the technical field of route planning. The ship route optimization method provided by the invention can predict the service life of key parts of an unmanned ship, find potential faults in advance, suggest maintenance measures through an early warning mechanism, and improve the safety of the unmanned ship. Through deep reinforcement learning and a distributed intelligent decision-making system, each unmanned ship can make an intelligent decision based on shared environment information and the state of the unmanned ship, cooperative avoidance of obstacles among fleets is realized, and meanwhile, the route of the unmanned ship is dynamically adjusted by using real-time weather forecast and environment change information, so that the unmanned ship is more intelligent. The method is advantaged in that the method is advantaged in that the method can better adapt to emergencies and environment changes, adaptability and flexibility of ship navigation, real-time environment perception and data sharing are improved, dynamic factors are considered in a planning stage through a distributed intelligent decision-making system, fleet collaborative decision-making is realized, and the method adapts to real-time changes of the marine environment.

The invention discloses a ship route planning method and system in a polar region sea ice environment and a program product. The ship route planning method comprises the steps of preprocessing satellite remote sensing radiation intensity data, performing image reconstruction of inter-ice water channel detection through an improved Vision Transform model, planning and visualizing a ship route and the like. The deep features of the image blocks are extracted through a Transformer encoder which comprises a multi-head self-attention mechanism and is processed by a multi-layer perceptron; and the Transform encoder firstly performs layer normalization on the input, and then performs multi-head attention mechanism and multiple linear transformation and regularization processing. And realizing path planning in an inter-ice water channel environment by fusing a dynamic planning cost function through a fast marching method. Compared with a traditional algorithm, the method has the advantages that the calculation precision is higher in the same scene, the calculation efficiency is greatly improved, and the planning result obtained after multiple costs are comprehensively considered is given instead of pursuing the shortest distance.

The invention discloses an automatic ship driving control method and system based on artificial intelligence, and relates to the technical field of ship control, and the driving control steps are as follows: S1, obtaining a current two-dimensional coordinate position of a ship based on a satellite map, and obtaining wind direction data of the current two-dimensional coordinate position in a ship route based on a weather bureau, obtaining a ship route state construction data set; and S2, establishing a ship running model, predicting position and attitude changes of the ship in a future route in combination with real-time wind direction data, calculating a ship displacement control quantity in advance through a control algorithm, and counteracting offset generated by wind direction factors. According to the invention, the ship can timely and accurately return to a correct route, the navigation accuracy of the ship in a complex environment is greatly improved, fine adjustment of ship navigation parameters is realized, unnecessary energy waste is avoided, deviation from a target route is avoided, and the risks of collision and stranding are increased.

The invention discloses a real-time dynamic ship route induction method for a ship in an inland river route network. The method comprises the following steps: collecting information; calculating the real-time dynamic speed of the ship and the interpenetration clearance of the ship; establishing a ship route network weighting topological graph; establishing a generalized path resistance function; establishing an induction path optimization model and solving an optimal route; and outputting a real-time dynamic ship induction route. The real-time dynamic induction route of the ship is calculated by establishing the ship route induction model on the basis of the real-time dynamic ship traffic flow prediction result in combination with the ship route network topological structure in the inland river route network, so that the method has the characteristics of high universality and wide coverage; the LSTM network is adopted to predict the ship navigational speed, the prediction precision is high, convergence is fast, and the workload is small; according to the invention, accurate real-time dynamic induction route information of the ship can be provided, and the reliability is good; due to the fact that the ant colony optimization algorithm of operational research is used for achieving real-time dynamic route planning of the ships in the inland river route network, economical efficiency is good.

The invention discloses a ship refined perception full-voyage track fitting and optimization method, which comprises the steps of drawing historical data acquired by an AIS (Automatic Identification System) to obtain a full-voyage-segment ship route track diagram, and dividing the full-voyage-segment ship route track diagram into a training set and a test set, the training set being used for generating an input image and a training label; based on the input image and the training label, loading historical weight parameters at the same time, and training to obtain a deep learning track separation model; testing set data is processed and then input into a deep learning track separation model, the model outputs an image, track data is cut and divided into a straight line stage and a curve stage, and track fitting is carried out in a segmented mode; combining the segmented tracks to obtain an overall track of the ship route; comparing the difference between the fitted curve and the actual curve, calculating a precision index, and if the precision is improved, iteratively updating a weight parameter of the deep learning trajectory separation model; otherwise, repeatedly training the iteration model until the precision index meets the requirement. According to the invention, the track features can be effectively identified, and the track fitting precision is effectively improved.

The invention relates to the field of ship route optimization, discloses a route optimization method and system based on a particle swarm optimization algorithm and geographic information, and is used for providing comprehensive decision support covering route planning, energy scheduling, risk control and carbon emission management for shipping enterprises. Comprising the steps that a commercial decision basic data set integrating geographic information, ship multi-energy system configuration and marine environment forecast data is constructed, and a commercial fractional order parameter set is generated; environment uncertainty is modeled by using a stochastic differential equation, a multi-energy system operation cost function is integrated, and a commercial cost prediction model capable of outputting operation cost probability distribution is formed; and carrying out risk-aware business strategy optimization based on a particle swarm optimization algorithm, and finally generating an executable business decision proposal containing a detailed route trajectory, a speed plan and a multi-energy equipment scheduling strategy. According to the invention, collaborative optimization of route planning and energy management is realized, and economy, safety and environmental protection of ship operation are significantly improved.

The invention discloses a ship route multi-target optimization model oriented to a composite sea condition scene, and relates to the technical field of ship route management, comprising the following steps of: acquiring ship navigation state data and marine environment data in real time by using marine monitoring equipment, a sensor network and ship equipment; establishing motion models of the ship under different sea conditions in combination with historical data; according to the method, the dynamic attitude model of the floating obstacle is constructed, dynamic changes such as rolling and pitching of the floating obstacle under the action of stormy waves are captured in real time, and a time-varying risk field is constructed in combination with a trajectory uncertainty ellipse. Compared with a traditional static obstacle processing mode, the model can accurately quantify real-time changes of the dynamic windward area, the resistance coefficient and the influence range of the obstacle, route planning errors caused by neglecting the dynamic characteristics of the obstacle are avoided, the movement state of the obstacle is updated in real time through the dynamic attitude vector, and the obstacle processing accuracy is improved. The ship can avoid the risk area expanded due to the posture change of the obstacle in advance, and the collision probability is remarkably reduced.

The invention belongs to the technical field of ocean measurement, and discloses a method and a system for measuring the sea surface height of deep and far sea based on Beidou PPP-B2b. The method comprises the following steps: calculating an antenna instantaneous geodetic height of a four-antenna GNSS receiver based on a WGS84 coordinate system; correcting the attitude of the buoy by using a buoy attitude correction algorithm to obtain the height of the buoy in the vertical direction; calculating the buoy draft according to a built-in instantaneous average water depth algorithm; the sea surface instantaneous height is calculated through a sea surface instantaneous height algorithm; carrying out noise reduction processing on the calculated instantaneous height of the sea surface through a filtering calculation unit; and the final result is sent to a monitoring service platform through a data transmission module. The method not only supports ship route planning and navigation safety, helps to avoid risks, but also provides long-term, stable and reliable data support for global climate change monitoring, marine environment protection and deep sea scientific research.

The invention relates to the technical field of energy system scheduling, in particular to a multi-port integrated energy system collaborative optimization scheduling method, system and device. According to the method, a ship transportation model is constructed, and ship route uniqueness, transportation duration, scheduling period position closed loop, port ship in-out balance and berth number limitation are restrained; establishing a mobile hydrogen storage model, and determining ship hydrogen charging and discharging mutual exclusion, a power effective range, hydrogen loading amount balance and safety, and correlation between berth priority and hydrogen loading amount; a multi-port comprehensive energy system collaborative optimization scheduling model is constructed by taking the lowest total cost of the multi-port comprehensive energy system including a ship berth priority comprehensive penalty term as a target, and the ship hydrogen loading amount and berth scheduling are bound. The operation flexibility and efficiency of the port comprehensive energy system are effectively improved.

The invention belongs to the technical field of ship scheduling optimization, and particularly relates to a container branch transport ship scheduling optimization method and system. The method comprises the steps of obtaining the number of ports and the number of ships for container transportation, setting algorithm parameters, initializing a population by utilizing Logistic chaotic mapping, decoding each individual, recording a historical optimal solution and a global optimal solution, entering a main loop to iteratively update individual positions, and starting an eagle positioning fishing mechanism and adaptive variation. A dynamic reverse learning mechanism calculates new fitness and an individual optimal position, and when the number of continuous stagnation times of the individual exceeds a threshold value, an escape mechanism is started, a golden section method is adopted to adjust departure time, 2-opt local search is performed on each ship route, a new position fitness value is evaluated, and an individual optimal solution is updated; if the maximum number of iterations is reached or a convergence threshold is met, outputting a global optimal solution; otherwise, returning to the main loop to continue iteration. The method can improve the performance of the algorithm in solving the scheduling optimization problem of the container branch transport ship.

The invention discloses a ship route planning method and system based on deep learning large-scale extreme wind speed forecast, and relates to the technical field of artificial intelligence and maritime navigation. An incremental principal component analysis method is introduced, a large-scale sea surface extreme wind speed forecasting model based on depth separable convolution is constructed, and potential physical sudden change disturbance information is decoded and reserved in a variable high-dimensional mapping space by the model through integration of an attention mechanism module and a residual learning algorithm; the attention mechanism module maps high-dimensional feature information in an extreme wind field time sequence to a multi-dimensional feature matrix of a coder-decoder. The method can perform refined dynamic forecasting on the large-scale sea surface extreme wind speed, accurately detect the extreme wind speed sea area and the boundary thereof, forecast and master the intermittent sudden change rule of the sea extreme wind speed in advance, help a ship driver to dynamically adjust the ship route in real time and avoid severe storm weather, and further ensure the navigation safety.

The invention relates to a ship route planning method and system integrating meteorological data and historical data, belongs to the technical field of ship route planning, and solves the problem of low feasibility of route planning caused by unreasonable space grid division and no consideration of meteorological data in the prior art. Comprising the steps that after historical route data are collected, a space diagram grid is constructed through downsampling and clustering; according to a to-be-planned route and ship information, space nodes corresponding to all the necessary passing points in the space diagram grids are obtained to serve as all the path points; predicting meteorological data and sea condition data of each space node in the space diagram grid, reconstructing the space diagram grid in combination with ship information, and calculating the weight of each edge in the reconstructed space diagram grid; and on the basis of the reconstructed space diagram grid, obtaining an optimal path passing through each path point according to the sequence of each path point and the weight of each edge, and then replacing each path point in the optimal path with each necessary point to obtain a planned route path. And safe and reliable ship route planning is realized.

The invention relates to a ship route automatic recommendation and matching method and system based on big data, and the method comprises the steps: receiving a starting point position and an end point position selected by a user, and automatically matching a corresponding nearest port as an actual starting point port and an actual end point port; generating a plurality of candidate routes in combination with historical navigation data, real-time meteorological data and ship performance parameters in the route database; carrying out adaptive analysis on the candidate routes based on the ship type and the cargo capacity, and excluding candidate routes which do not conform to ship navigation conditions; performing multi-dimensional evaluation on the candidate airlines through a preset optimization algorithm, generating an airline recommendation list, and sending the airline recommendation list to a user interface; and continuously monitoring the real-time state data of the route selected by the user, and triggering an automatic re-planning process if detecting that the channel is abnormal or the weather is suddenly changed. According to the method, big data analysis, intelligent matching and dynamic optimization are integrated, and automatic, multi-dimensional and high-reliability route recommendation and collaborative management are realized.

The invention relates to the technical field of ship route planning, in particular to a ship navigation real-time optimal route planning method based on an improved genetic algorithm, and the method comprises the steps: obtaining an input data set containing ship static parameters, multi-period environment prediction data and navigation constraints; an improved path search algorithm based on a comprehensive cost function is adopted to process input data, an initial navigation path is generated, and the cost function synchronously considers leg length, navigation risk and violation penalty. And carrying out speed scheme optimization on the initial path by adopting an improved genetic algorithm containing specific chromosome coding and a multi-target fitness function to generate an optimal speed distribution scheme. And fusing the initial path and the speed scheme, and outputting a route planning result containing a route point sequence and the recommended navigational speed of each route segment. According to the invention, integrated collaborative optimization of the path and the speed is realized.

The invention relates to the field of intelligent shipping, in particular to a ship route tidal window passage calculation method and system, and the method comprises the steps: obtaining the navigation parameters of a ship and the hydrological geographic information of a target route; calculating the minimum safe water depth required by the ship in the sailing process based on the sailing parameters; predicting the tidal height change of at least one tidal point on the target route in a period of time in the future based on the hydrological geographic information; the actual water depth change of the tidal point in a period of time in the future is dynamically determined in combination with the tidal height change and hydrological geographic information; performing comparative analysis on the actual water depth change and the minimum safe water depth, and generating one or more passable time windows of the tidal point according to an analysis result; and outputting a passable time window for ship navigation decision. According to the method, multiple factors such as ship sinkage, waves, ship swing and safety reserve are comprehensively considered, the dynamically calculated minimum safety water depth is more scientific and comprehensive, and risks possibly brought by fixed safety margin are avoided.

The invention discloses a ship transportation nickel ore route optimization method considering risk and emission, and the method comprises the steps: S1, obtaining risk factors affecting nickel ore liquefaction in marine transportation of nickel ore, and taking the risk factors as network nodes to construct an initial Bayesian network affecting a nickel ore liquefaction risk state; s2, obtaining historical event data of nickel ore marine transportation, and training the initial Bayesian network based on the historical event data to obtain a Bayesian risk inference network; s3, performing sensitivity analysis on each network node according to the conditional probability to obtain a key network node, and obtaining a risk numerical map of a ship transportation nickel ore route based on the key network node; s4, on the basis of the risk value map, assumed conditions for ship nickel ore transportation route optimization are set; s5, constructing a ship route transportation multi-objective optimization model according to assumed conditions; and S6, taking the lowest ship route transportation risk, the lowest energy consumption and the lowest emission as optimization objectives, based on an improved NSDBO algorithm, according to the ship route transportation multi-objective optimization model, solving and obtaining an optimal solution corresponding to the optimization objectives, and according to the optimal solution, realizing ship transportation nickel ore route optimization considering the risk and the emission. The nickel ore liquefaction risk assessment system solves the problem that a process for systematic risk assessment of nickel ore liquefaction is lacked in previous researches, and meanwhile, in the aspect of measures for coping with nickel ore liquefaction risks, previous researchers tend to reduce the probability of nickel ore liquefaction and the caused adverse effects by improving a ship structure and adjusting ship safety management, and the risk assessment efficiency is improved. And the method for improving the nickel ore transportation safety and environmental performance by optimizing the route design is lacked.

The invention provides a ship route planning model training method and a related device. An electronic device obtains a current observation state of a ship intelligent body; wherein the observation state comprises an obstacle observed by the ship intelligent body; according to the observation state, the collision risk between the ship intelligent body and the obstacle is determined; the observation state and the collision risk are processed through the ship intelligent body, and a navigation strategy for the observation state and the collision risk is obtained; generating a strategy reward of the navigation strategy according to the navigation strategy; and updating the ship agent according to the strategy reward. Thus, the observation state containing the dynamic obstacle is obtained, and the collision risk between the ship intelligent body and the obstacle is evaluated based on the observation state, so that the model has the capability of identifying time-varying risk factors such as front floating ice and sea fog, thereby dynamically responding to the multi-source time-varying risk in the north pole complex environment, and improving the real-time performance and safety of route planning.

The embodiment of the invention discloses a ship route data extraction method and device based on AIS (Automatic Identification System) data. The method comprises the following steps: collecting historical ship route data to obtain a ship navigation path; performing route feature recognition according to the historical ship route data to obtain route features, dividing route segments based on the route features, and classifying different route segments; and performing clustering processing on the classified route segments, and performing segment processing on the clustered route segments to obtain an empirical route data set. Based on the historical AIS data of the ship, the method can reflect the real navigation habit of the ship, and accords with the navigation management regulations of near-shore and navigable water channel areas. When the method is adopted to process the airline data, a complicated data cleaning process is not needed, and the consistency from original data to generalized data is easy to ensure; the route data are recombined after being subjected to segmented fitting, so that route selection between two ports is more flexible; a conservative method is adopted to process AIS data, and experience and intelligence of ship route selection are reserved in the data.

The present invention relates to a method for providing an optimal boat route. The method for providing an optimal boat route, executed through an operating server that provides an optimal boat route in real time according to the present invention, comprises: a first step of collecting real-time location and movement data of a boat and marine environment data; a second step of analyzing current navigation conditions based on the collected data and calculating an optimal route using the analyzed data; a third step of transmitting the calculated optimal route to a terminal equipped on the boat or to a user's terminal; and a fourth step of recalculating the route according to real-time environmental changes and continuously updating it.

The invention discloses a ship safe navigation monitoring method based on a video image, and the method comprises the steps: 1, obtaining a video frame in real time through a ship-borne camera, and carrying out the preprocessing of the video frame; step 2, identifying and positioning a target position in a video frame through a fusion positioning algorithm; 3, calculating the distance between the ship and the target according to the detected target position; 4, track prediction is carried out on the detected target, and the future position and the motion path of the target are estimated; 5, calculating potential collision time according to the relative positions of the ship and the target and the speed and trajectory of the target, and if the potential collision time is smaller than a preset safety threshold value, judging that a collision risk exists; and step 6, when a potential collision risk is detected, the system generates an early warning signal to remind a ship driver to take actions. According to the invention, the accuracy of target identification on the ship route is improved, so that the shipping safety is improved.

The present disclosure relates to modifying a ship route, comprising: at a user interface, presenting a map (2) comprising a proposed future route (1a) for a ship (3); via the user interface, receiving input from a user, the input including at least one request for modifying a route property of the presented route and / or at least one request for modifying a predefined constraint on a ship property among a plurality of predefined constraints on ship properties; at a processing device, recalculating the proposed route based on the received request(s) and on the predefined constraints on ship properties; and, at the user interface, presenting the recalculated route (1b) on the map.

The invention belongs to the field of ship automation control, and provides a ship route generation method and device based on artificial intelligence, equipment and a storage medium. The method comprises the following steps: constructing a route generation model based on deep reinforcement learning training to generate a waypoint set, and connecting a plurality of waypoints in the waypoint set into a route; when a rudder angle control vector is generated by applying an action to a ship according to a course, based on a fuzzy rule, taking a course angle error, a speed and an acceleration as input, and performing fuzzy calculation to obtain a first rudder angle control increment; whether environment disturbance exists or not is determined based on a Kalman filter, when the environment disturbance exists, a second rudder angle control increment is obtained after calculation based on a fuzzy rule, and the first rudder angle control increment, the second rudder angle control increment and a rudder angle control vector are combined to control ship operation; the invention aims to realize optimal route planning and accurate path following of the ship in autonomous navigation through a reinforcement learning algorithm and fuzzy control, ensure navigation safety and reduce fuel consumption.

The present invention relates to the technical field of route planning, and discloses a method, system, device, and medium for dividing a navigation area adaptive to sea conditions. The present invention first obtains a great circle route with the shortest navigation distance of a target ship in a target navigation area based on navigation data of a target ship, then obtains accurate and true spatiotemporal sea condition data based on the navigation data on the great circle route using a spatiotemporal interpolation method, and then iteratively clusters the spatiotemporal sea condition data using a clustering algorithm with improved weight coefficients for sea condition characteristics to obtain refined cluster clusters. This method can achieve accurate and refined navigation area division, provide reliable data support for ocean-going vessel route optimization and unmanned vessel path planning, and further improve the quality of ocean-going vessel route optimization and unmanned vessel path planning.

The embodiment of the present application provides a navigation trajectory prediction method, a computer storage medium and a program product. The navigation trajectory prediction method includes: obtaining port location data and historical ship route data, wherein the historical ship route data includes historical navigation trajectory points of the ship; according to the port location data, determining the historical navigation trajectory points that match the port location from the historical ship route data; using the historical navigation trajectory points that match the port location as endpoints, segmenting the historical ship route data, obtaining historical route data marked with historical departure ports and historical destination ports, so as to determine the historical departure port that is the same as the departure port of the current voyage of the target ship, and predicting the navigation trajectory of the target ship according to the historical route data corresponding to the historical departure port.

The present disclosure relates to modifying a ship route, comprising: at a user interface, presenting a map (2) comprising a proposed future route (1a) for a ship (3); via the user interface, receiving input from a user, the input including at least one request for modifying a route property of the presented route and / or at least one request for modifying a predefined constraint on a ship property among a plurality of predefined constraints on ship properties; at a processing device, recalculating the proposed route based on the received request(s) and on the predefined constraints on ship properties; and, at the user interface, presenting the recalculated route (1b) on the map.

To create a vessel allocation plan that reduces transportation costs while suppressing the number of port calls.SOLUTION: A server apparatus (2) for deriving a vessel allocation plan for transporting raw materials from a plurality of loading ports to unloading ports by a plurality of vessels includes: an acquisition unit (21) configured to acquire information regarding a plurality of loading port groups, each of which is formed by grouping a plurality of loading ports; a setting unit (22) configured to set, as an index corresponding to each loading port group, an index including parameters relating to the vessel allocation plan as variables, the index indicating the total number of port calls made by vessels to the loading ports belonging to the loading port group. When one vessel calls at a plurality of loading ports belonging to the same loading port group, the number of port calls of the vessel is counted as a smaller number than the number of the plurality of ports; and a calculation unit (23) configured to derive each parameter relating to the vessel allocation plan so that the value of an objective function, which is defined as the sum of terms corresponding to the indices for the loading port groups, is minimized.SELECTED DRAWING: Figure 3

The invention relates to an auxiliary decision-making method for ship fuel selection, which breaks through a traditional route division mode singly based on geographic distance or time, integrates docking ports, predicted navigation time, geographic position information, regulation region boundaries and fuel information conditions in a ship route plan, breaks through the traditional route division mode, and improves the ship fuel selection efficiency. Finely dividing the set route into a plurality of small route segments; according to the division mode, the actual conditions of all the legs can be accurately matched, and a more accurate basis is provided for follow-up fuel selection. When fuel is selected in each leg, factors in multiple aspects such as fuel cost, regulatory requirements and operation states (such as cargo capacity) of the ship are comprehensively balanced. And different fuels are flexibly switched and used, so that the optimal balance between the economical efficiency and compliance of ship operation is realized. The relevance between different legs and dynamic changes of laws and regulations and cost are fully considered, the purpose of lowest total fuel cost is achieved from the global perspective, and meanwhile it is ensured that the ship strictly meets the requirements of the laws and regulations all the time.