Navigation speed optimization method applied to ship, server, medium and product

Abstract

The embodiment of the invention discloses a navigational speed optimization method applied to a ship, a server, a medium and a product, and the method comprises the steps: determining at least one group of predicted meteorological data according to the navigation data of a target ship; according to the at least one group of predicted meteorological data, the draught data of the target ship and the at least one rotating speed group, determining a total fuel consumption attribute corresponding to the target ship under each rotating speed group; wherein the at least one rotating speed group comprises a plurality of rotating speeds, the rotating speeds in the same time slice are the same, and the time slice is divided according to the navigation data of the target ship; and determining a target rotating speed group from the at least one rotating speed group according to the total oil consumption attribute, and controlling the navigation speed of the target ship according to the rotating speed in the target rotating speed group. According to the technical scheme provided by the embodiment of the invention, the effect of optimal navigational speed is achieved under the condition of meeting the period ship renting contract.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of ship data processing, and in particular to a speed optimization method, a server, a medium and a product applied to a ship. Background Art

[0002] Time charter is a common ship leasing model. In this model, fuel consumption is a key clause in the leasing model, which involves the fuel usage and cost sharing of the ship.

[0003] Usually, the charterer can sign a contract with the shipowner (the user who leases the ship). The contract can clearly state the theoretical speed and theoretical fuel consumption standards when the ship is fully loaded or empty.

[0004] At present, most speed optimizations focus on fuel saving, ignoring the diversity of ship operating models, that is, not considering the constraints of speed and fuel consumption in the contract, resulting in the problem of not being able to maximize the interests of shipowners. Summary of the invention

[0005] The embodiments of the present invention provide a method, a server, a medium and a product for optimizing the speed of a ship, so as to achieve the effect of optimizing the speed of the ship according to the constraints in the time charter contract.

[0006] In a first aspect, an embodiment of the present invention provides a speed optimization method applied to a ship, the method comprising:

[0007] Determine at least one set of forecast meteorological data according to the navigation data of the target ship;

[0008] Determine the total fuel consumption attribute corresponding to the target ship in each speed group according to the at least one set of predicted meteorological data, the draft data of the target ship, and at least one speed group; wherein the at least one speed group includes multiple speeds, and the speeds in the same time slice are the same, and the time slice is divided according to the navigation data of the target ship;

[0009] According to the total fuel consumption attribute, a target speed group is determined from the at least one speed group, so as to control the sailing speed of the target ship according to the speed in the target speed group.

[0010] Furthermore, the method further comprises:

[0011] Determining at least one time slice according to the navigation time in the navigation data;

[0012] Determine the speed corresponding to each time slice based on the covariance optimization algorithm;

[0013] According to the speed corresponding to each time slice, a speed group is determined;

[0014] The covariance optimization algorithm is continuously used to update the rotation speed corresponding to each time slice to obtain multiple rotation speed groups.

[0015] Furthermore, determining at least one set of forecast meteorological data according to the navigation data of the target ship includes:

[0016] Determine at least one time point and the longitude and latitude data corresponding to the time point according to the estimated departure time and the estimated arrival time in the navigation data;

[0017] Determining the forecasted meteorological data for each time point based on the latitude and longitude data of the at least one time point;

[0018] The predicted meteorological data includes at least one of wind speed, wind direction, wave height, wave direction and water flow rate.

[0019] Further, determining the total fuel consumption attribute corresponding to the target ship in each speed group according to the at least one set of predicted meteorological data, the draft data of the target ship, and at least one speed group includes:

[0020] For the at least one speed group, the speed group, the predicted meteorological data and the draft data are input into a pre-trained speed and fuel consumption prediction model to output the fuel consumption and speed corresponding to the target ship in each time slice under the speed group;

[0021] When the fuel consumption and the rotation speed meet preset constraints, a total fuel consumption attribute of the target ship is determined.

[0022] Furthermore, the preset constraints include:

[0023] The fuel consumption satisfies a preset fuel consumption constraint condition;

[0024] When the predicted meteorological data meets the preset meteorological constraint condition, the navigation speed meets the preset navigation speed threshold;

[0025] The mileage of the target ship reaches a preset mileage constraint within a preset time period.

[0026] Further, determining the target speed group from the at least one speed group according to the total fuel consumption attribute includes:

[0027] The minimum total fuel consumption attribute is used as the target total fuel consumption attribute, and the speed group corresponding to the target total fuel consumption attribute is used as the target speed group.

[0028] Furthermore, the method further comprises:

[0029] If the target speed group is not determined, adjusting the estimated arrival time in the navigation data to determine the predicted weather data and the speed group at each time point based on the updated estimated arrival time;

[0030] The step of determining a target speed group corresponding to the target ship based on the updated predicted meteorological data and the updated speed group.

[0031] In a second aspect, an embodiment of the present invention further provides a speed optimization device for use in a ship, the device comprising:

[0032] A forecast meteorological data determination module, used to determine at least one set of forecast meteorological data according to the navigation data of the target ship;

[0033] a total fuel consumption attribute determination module, configured to determine the total fuel consumption attribute corresponding to the target ship in each speed group according to the at least one group of predicted meteorological data, the draft data of the target ship, and at least one speed group; wherein the at least one speed group includes a plurality of speeds, and the speeds in the same time slice are the same, and the time slice is divided according to the navigation data of the target ship;

[0034] The sailing speed optimization module is used to determine a target speed group from the at least one speed group according to the total fuel consumption attribute, so as to control the sailing speed of the target ship according to the speed in the target speed group.

[0035] In a third aspect, an embodiment of the present invention provides a server, which includes:

[0036] one or more processors;

[0037] A memory for storing one or more programs;

[0038] When the one or more programs are executed by the one or more processors, the one or more processors implement the speed optimization method applied to a ship as provided in any embodiment of the present invention.

[0039] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a speed optimization method applied to a ship as provided in any embodiment of the present invention.

[0040] In a fifth aspect, an embodiment of the present invention further provides a computer program product, including a computer program, characterized in that when the computer program is executed by a processor, it implements the speed optimization method applied to a ship as described in any one of the embodiments of the present invention.

[0041] The technical solution provided by the embodiment of the present invention can determine at least one set of predicted meteorological data that matches the navigation data by analyzing the acquired navigation data of the target ship. Next, the total fuel consumption attribute corresponding to the target ship under each speed group can be determined by analyzing and processing the at least one set of predicted meteorological data, the draft data of the target ship, and the generated at least one speed group. According to the total fuel consumption attribute and the fuel consumption and speed in the pre-set time charter contract, a target speed group can be determined from at least one speed group to control the travel of the target ship based on the target speed group, so as to achieve the effect of optimizing the navigation data under the conditions of the time charter contract. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required to describe the embodiments. Obviously, the drawings introduced are only drawings of a part of the embodiments to be described in the present invention, rather than all the drawings. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0043] Figure 1 A flow chart of a method for optimizing ship speed provided by an embodiment of the present invention;

[0044] Figure 2 A flow chart of a method for optimizing ship speed provided by an embodiment of the present invention;

[0045] Figure 3 A schematic diagram of the structure of a speed optimization device applied to a ship provided by an embodiment of the present invention;

[0046] Figure 4 A schematic diagram of the structure of a server provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0048] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0049] Before introducing the technical solution provided by the embodiment of the present invention, an exemplary application scenario can be first described. The speed of the target ship can be optimized in combination with the theoretical speed and theoretical fuel consumption in the time charter contract to maximize the interests of the shipowner and the charter user. The specific implementation method can refer to the detailed description of this technical solution.

[0050] Figure 1 A flow chart of a speed optimization method applied to a ship provided in an embodiment of the present invention. This embodiment can be applicable to any scenario where it is necessary to optimize the navigation speed of a target ship based on a time charter contract. The speed optimization method applied to a ship provided in this embodiment can be executed by a client, or by a server, or by a client and a server in cooperation.

[0051] like Figure 1 As shown, the method specifically comprises the following steps:

[0052] S110. Determine at least one set of predicted meteorological data according to the navigation data of the target ship.

[0053] The speed optimization method for each ship is the same, and the ship currently introduced can be used as the target ship. The navigation data includes the departure time, arrival time, departure position (departure position) and target position of the target ship. The number of at least one set of forecast meteorological data can include one or more groups, and the specific number of groups is related to the division of the navigation data.

[0054] Specifically, at least one stop time point can be determined for the departure time and arrival time in the navigation data of the target ship. Pre-predicted meteorological data can be retrieved according to the location of the target ship at the stop time point, and the meteorological data can be used as the predicted meteorological data for the stop time point.

[0055] In this embodiment, at least one set of predicted meteorological data is determined based on the navigation data of the target ship, including: determining at least one time point and the longitude and latitude data corresponding to the time point based on the estimated departure time and the estimated arrival time in the navigation data; determining the predicted meteorological data for each time point based on the longitude and latitude data of at least one time point; wherein the predicted meteorological data includes at least one of wind speed, wind direction, wave height, wave direction and water flow rate.

[0056] The estimated departure time in the navigation data is the departure time of the target ship. The estimated arrival time is the preset time when the target ship arrives at the destination. The time length between the estimated departure time and the estimated arrival time can be divided according to the preset division granularity to obtain multiple time segments. The starting point and the end point of each time segment correspond to a time point. The position that the target ship can reach at each time point can be estimated, and the longitude and latitude data of the target ship's position at each time point can be obtained. The predicted meteorological data of the target ship can be retrieved based on the longitude and latitude data.

[0057] It should also be noted that, based on the starting position and the destination position in the navigation data, the position interpolation process can be performed to obtain multiple position points. According to the latitude and longitude data corresponding to the position points, the corresponding forecast weather data can be retrieved.

[0058] In this embodiment, since the target ship is at sea, the predicted meteorological data should include at least one of wind speed, wind direction, wave height, wave direction and water flow rate.

[0059] The wind speed may be at least one or more of sea breeze speed, sea breeze blowing direction, wave height, wave wind direction and water flow speed.

[0060] Specifically, multiple stop time points corresponding to the target ship can be determined based on the navigation data. The longitude and latitude data corresponding to each stop time point can be determined. The forecasted meteorological data corresponding to the longitude and latitude data can be retrieved.

[0061] For example, the estimated departure time of the target ship is A, the estimated arrival time is B, the starting position is C, and the destination position is D. The starting position C and the destination position D can be interpolated to obtain multiple interpolated position points. The longitude and latitude data corresponding to each interpolated position point are obtained. The predicted meteorological data corresponding to each longitude and latitude data are retrieved. Alternatively, at least one time point can be determined based on the estimated departure time A and the estimated arrival time B. Based on the longitude and latitude data of the position that can be reached at each time point in theory, its predicted meteorological data can be retrieved.

[0062] It should be noted that the number of groups of predicted meteorological data is related to the number of time points and the number of interpolation location points.

[0063] S120: Determine a total fuel consumption attribute corresponding to the target ship in each speed group according to at least one group of predicted meteorological data, the draft data of the target ship, and at least one speed group.

[0064] At least one speed group includes multiple speeds, and the speeds in the same time slice are the same. The time slice is divided according to the navigation data of the target ship.

[0065] The draft data includes the bow draft data of the target ship and the stern draft data of the target ship. Each speed group may include multiple speeds. The speeds of the target ships are the same within the same time slice range. Alternatively, after position interpolation processing, the speeds of the target ships within the same position range are the same. The ship speed optimization method that can be used is used to process each group of ship speeds to obtain multiple speed groups.

[0066] It should be noted that the processing method for each speed group is the same, and at least one set of predicted meteorological data, the draft data of the target ship, and multiple speeds in the speed group can be processed to obtain the total fuel consumption attributes of the target ship in each speed group.

[0067] Specifically, by processing at least one set of predicted meteorological data of the target ship, the draft data of the target ship, and a plurality of rotational speeds in the rotational speed group, the total fuel consumption attribute corresponding to the target ship in each rotational speed group can be obtained.

[0068] For example, the navigation data of the target ship can be divided into 1000 position points, and the rotation speed between two position points can be generated, that is, 1000 rotation speeds can be obtained. The rotation speed of the driving section corresponding to the two position points is the same. By processing the 1000 rotation speeds, the obtained predicted meteorological data, and the draft data of the target ship in the initial state, the total fuel consumption attribute of the target ship under the rotation speed group is obtained.

[0069] In this embodiment, the method for determining at least one speed group corresponding to the target ship can be: determining at least one time slice based on the navigation time in the navigation data; determining the speed corresponding to each time slice based on the covariance optimization algorithm; determining a speed group based on the speed corresponding to each time slice; and continuously using the covariance optimization algorithm to update the speed corresponding to each time slice to obtain multiple speed groups.

[0070] It can be understood that: the navigation time in the navigation data can be divided into half-hour granularity to obtain multiple time slices. The covariance optimization algorithm can be used to generate the speed corresponding to each time slice. By splicing the speed corresponding to each time slice, a speed group is obtained. The speed group can include multiple speeds. The covariance optimization algorithm can be continuously used to update the speed corresponding to each time slice to obtain multiple speed groups.

[0071] After obtaining multiple speed groups, the predicted fuel consumption and predicted speed under each speed group can be determined. Based on the predicted fuel consumption, predicted speed and the constraints set in the contract, it can be determined whether to determine its total fuel consumption attribute. If the predicted fuel consumption and predicted speed can meet the constraints set in the contract, the total fuel consumption attribute under this speed group can be determined. If the predicted speed and predicted fuel consumption fail to meet the constraints set in the contract, it means that this speed group fails to meet the contract constraints and can be discarded and its total fuel consumption attribute is no longer determined.

[0072] In this embodiment, determining the total fuel consumption attribute corresponding to the target ship in each speed group can be: for at least one speed group, the speed group, predicted meteorological data and draft data are input into a pre-trained speed and fuel consumption prediction model to output the fuel consumption and speed corresponding to the target ship in each time slice under the speed group; when the fuel consumption and speed meet the preset constraints, the total fuel consumption attribute of the target ship is determined.

[0073] The speed fuel consumption prediction model is pre-trained and used to process the input data to output a model for predicting fuel consumption and speed. Optionally, a speed fuel consumption prediction model generated by a support vector machine machine learning algorithm may be used. The preset constraints may be constraints set according to the time charter contract.

[0074] It should be noted that the contents of each time charter contract may be the same or different. Accordingly, the constraints for different ships may also vary to a certain extent.

[0075] Specifically, for each speed group, multiple speeds, predicted meteorological data and draft data in the speed group can be input into a pre-trained speed and fuel consumption prediction model, which can output the fuel consumption and speed corresponding to the target ship at each time slice.

[0076] In this embodiment, the fuel consumption satisfies the preset fuel consumption constraint; when the predicted meteorological data satisfies the preset meteorological constraint, the speed satisfies the preset speed threshold; and within the preset time, the mileage of the target ship reaches the preset mileage constraint.

[0077] The preset meteorological constraint condition may be that the wind speed is less than the preset wind speed threshold, the wind direction is less than the preset wind direction threshold, the wave height is less than the preset wave height threshold, and the water flow rate is less than the preset flow rate threshold. The preset speed threshold is the speed set in the charter contract. The preset fuel consumption constraint condition is that the fuel consumption is less than the preset fuel consumption threshold. The preset duration may be the duration from the estimated departure time to the estimated arrival time. The preset mileage constraint condition is the total mileage from the departure location to the arrival location.

[0078] Specifically, after determining the predicted speed and predicted fuel consumption under a certain speed group based on the speed and fuel consumption prediction model, the predicted meteorological data corresponding to each time slice can be obtained. Determine the target meteorological data that meets the preset meteorological constraints from all predicted meteorological data. Retrieve the speed corresponding to the target meteorological data. If the speed reaches the preset speed threshold, it means that the first preset constraint is met. Further, it can be determined whether the fuel consumption is less than the preset fuel consumption threshold in the preset fuel consumption constraint. If so, it means that it meets the second constraint in the preset constraint. The mileage of the target ship within the preset time period can be calculated. If the mileage is greater than the total mileage in the preset mileage constraint, it means that the speed under the speed group meets the corresponding requirements.

[0079] It should be noted that if all the conditions in the preset constraints are met, it can be determined that the speed and fuel consumption under the speed meet the conditions, and its total fuel consumption attribute can be determined. On the contrary, if any condition in the preset constraints is not met, it means that the speed group is unavailable, and it can continue to re-determine whether the speed and fuel consumption corresponding to the next speed meet the preset constraints.

[0080] S130. Determine a target speed group from at least one speed group according to the total fuel consumption attribute, so as to control the navigation speed of the target ship according to the speed in the target speed group.

[0081] The target speed group is the speed group to be used by the target ship finally selected.

[0082] Specifically, the number of speed groups that meet the preset constraint conditions may include one or more groups, and the total fuel consumption attribute corresponding to each speed group that meets the preset constraint conditions may be obtained respectively. The speed group corresponding to the minimum total fuel consumption attribute is used as the target speed group. The speed corresponding to the target speed group may be used as the navigation speed used by the target ship.

[0083] In the present invention, determining the target speed group from at least one speed group according to the total fuel consumption attribute includes: taking the minimum total fuel consumption attribute as the target total fuel consumption attribute, and taking the speed group corresponding to the target total fuel consumption attribute as the target speed group.

[0084] It can be understood that: for the speed groups that meet the preset constraints, the total fuel consumption attributes corresponding to each speed group may be different, and the minimum total fuel consumption attribute is taken as the target total fuel consumption attribute. The speed group corresponding to the target total fuel consumption attribute is taken as the target speed group.

[0085] After the target rotation speed group is obtained, the target ship can be controlled to control the travel speed of the target ship according to the rotation speed group.

[0086] Based on the above technical solution, the method also includes: if the target speed group is not determined, adjusting the estimated arrival time in the navigation data to determine the predicted meteorological data and speed group for each time point based on the updated estimated arrival time; based on the updated predicted meteorological data and the updated speed group, determining the target speed group corresponding to the target ship.

[0087] It can be understood that: if the target speed group corresponding to the target ship is not determined based on the above method, and the normal performance of the contract can be guaranteed, the estimated arrival time in the navigation data can be adjusted to adjust the preset duration in the preset constraint condition based on the adjusted estimated arrival time. The predicted meteorological data and multiple speeds in at least one predicted speed group can be re-determined based on the updated estimated arrival time. The step of re-determining the target speed group corresponding to the target ship can be performed based on the updated data.

[0088] In this embodiment, the navigation speed corresponding to the target rotation speed group may be used as the optimized target navigation speed for the target ship.

[0089] The technical solution provided by the embodiment of the present invention can determine at least one set of predicted meteorological data that matches the navigation data by analyzing the acquired navigation data of the target ship. Next, the total fuel consumption attribute corresponding to the target ship under each speed group can be determined by analyzing and processing the at least one set of predicted meteorological data, the draft data of the target ship, and the generated at least one speed group. According to the total fuel consumption attribute and the fuel consumption and speed in the pre-set time charter contract, a target speed group can be determined from at least one speed group to control the travel of the target ship based on the target speed group, so as to achieve the effect of optimizing the navigation data under the conditions of the time charter contract.

[0090] As an alternative embodiment of the above embodiment, Figure 2 A flow chart of a speed optimization method applied to a ship provided in an embodiment of the present invention can be illustrated by taking a specific example on the basis of the aforementioned embodiment. Its specific implementation method can refer to the detailed description of this embodiment, wherein the technical terms that are the same as or corresponding to the aforementioned embodiment are not repeated in this embodiment.

[0091] The functional goal of the embodiment of the present invention is to assist the time charter ship to meet the speed and fuel consumption requirements in the contract, and to provide an expected arrival time. The optimization goal is to achieve the optimal speed combination with the lowest fuel consumption during the entire voyage while satisfying the preset constraints.

[0092] In this embodiment, the preset constraint conditions may be: the hourly fuel consumption of the entire journey meets the fuel consumption requirements specified in the time charter contract. Under "good weather" conditions, the hourly speed of the ship meets the requirements specified in the time charter contract. The ship completes the total voyage within the departure and arrival time range of the voyage plan.

[0093] Among them, the hourly fuel consumption in the contract can be the preset fuel consumption threshold in the preset fuel consumption constraint. The fuel consumption corresponding to each time slice can be obtained, and the predicted fuel consumption corresponding to each hour can be obtained based on the time length corresponding to the time slice. Based on the predicted fuel consumption and the preset fuel consumption threshold, it can be determined whether it meets the preset constraint. The preset meteorological constraint is the meteorological data corresponding to "good weather". The definition of "good weather" can be found in the detailed description of the above embodiment. The predicted speed in good weather is obtained, and when the predicted speed meets the preset speed threshold, it means that it meets the speed constraint in the lease contract. Furthermore, the total voyage completed corresponds to the mileage data between the departure point and the destination point in the navigation data of the target ship. If the mileage from the departure time point to the end time point determined based on the predicted speed is consistent with the total mileage, it means that it meets the preset mileage constraint in the preset constraint.

[0094] In summary, the speed corresponding to the above preset constraints is taken as the final speed of the target ship.

[0095] See also Figure 2 , you can first obtain the draft data of the target ship in the initial state. The draft data includes the bow draft data and the stern draft data. The route is the navigation data of the current voyage of the target ship. Optionally, the navigation data includes the departure time, arrival time, departure position and destination position of the target ship. By interpolating the departure position and the destination position, multiple position points can be obtained. Or, based on the interpolation processing of the departure time and the arrival time, multiple interpolation time points are obtained. The predicted meteorological data can be obtained based on the longitude and latitude data of multiple position points. Or, based on each interpolation time point, the corresponding longitude and latitude data is determined, and the predicted meteorological data corresponding to the longitude and latitude data is obtained.

[0096] The predicted meteorological data includes the wind speed and direction that the target ship may encounter at each longitude and latitude data, the wave height and direction encountered, and the current speed encountered by the target ship.

[0097] Furthermore, the rotation speed values ​​in different time slices or at different longitude and latitude data may be determined based on the covariance optimization algorithm, so as to obtain a rotation speed group based on the rotation speed values ​​corresponding to the different time slices.

[0098] Multiple rotation speeds in the rotation speed group, predicted gas phase data, and draft data can be input into a speed and fuel consumption prediction model, and the model can predict fuel consumption and speed.

[0099] In other words: the speed and fuel consumption prediction model based on the support vector machine (SVR) machine learning algorithm processes the data to obtain the predicted fuel consumption and predicted speed.

[0100] The input parameters of the speed fuel consumption prediction model may include: ship speed (multiple speeds in the speed group), ship's bow / stern draft data, ship's encounter wave height / wave direction, ship's encounter wind speed / wind direction, ship's encounter flow speed, water depth and other data. The ship's bow / stern draft is directly obtained from the sailing plan. The ship's encounter wave height / wave direction, ship's encounter wind speed / wind direction, and ship's encounter flow speed are provided by the route, departure and arrival time in the sailing plan, respectively, providing the location and time of the ship's encounter with weather in the future voyage, and are interpolated in the weather forecast database. At least one speed in the speed group is obtained by generating a large number of speed combinations within the allowable range of ship performance by the CMA-ES covariance optimization algorithm. That is, a speed group is first randomly generated, and then on this basis, the covariance optimization algorithm is used to optimize the speed in the speed group to obtain multiple speed groups.

[0101] In this embodiment, the entire navigation plan can be divided according to time, and a speed is matched for each time period. Based on this, the entire navigation plan corresponds to a speed combination. The CMA-ES covariance optimization algorithm continuously generates speed groups, and calculates whether they meet the above optimization constraints, and finally finds the speed combination that optimizes the fuel consumption of the entire journey under the premise of meeting the optimization constraints.

[0102] After obtaining the speed and fuel consumption of a certain speed group based on the speed and fuel consumption prediction model, it is possible to further calculate whether the speed and fuel consumption meet the preset constraints. If the preset constraints are met, the total fuel consumption attribute is calculated; if the preset constraints are not met, the speed group can be ignored, and the steps of calculating the speed and fuel consumption corresponding to the next speed group can be continued.

[0103] All the total fuel consumption attributes obtained can be sorted, and the speed group corresponding to the minimum total fuel consumption attribute is used as the target speed group. Correspondingly, the speed corresponding to the target speed group is used as the target speed of the target ship.

[0104] It should be noted that if the target speed group is not determined based on the above method, the arrival time can be adjusted to redetermine the speed group and the preset constraint condition based on the adjusted arrival time. According to the adjusted speed group and the preset constraint condition, the target speed group corresponding to the target ship is redetermined to determine the optimal speed of the target ship based on the target speed group.

[0105] The technical solution provided by the embodiment of the present invention can determine at least one set of predicted meteorological data that matches the navigation data by analyzing the acquired navigation data of the target ship. Next, the total fuel consumption attribute corresponding to the target ship under each speed group can be determined by analyzing and processing the at least one set of predicted meteorological data, the draft data of the target ship, and the generated at least one speed group. According to the total fuel consumption attribute and the fuel consumption and speed in the pre-set time charter contract, a target speed group can be determined from at least one speed group to control the travel of the target ship based on the target speed group, so as to achieve the effect of optimizing the navigation data under the conditions of the time charter contract.

[0106] The following is an embodiment of a speed optimization device applied to a ship provided by an embodiment of the present invention. The device and the speed optimization method applied to a ship in the above embodiments belong to the same inventive concept. For details not described in detail in the embodiment of the speed optimization device applied to a ship, reference can be made to the embodiment of the speed optimization method applied to a ship in the above embodiments.

[0107] Figure 3 The present invention provides a schematic structural diagram of a speed optimization device for use in a ship according to an embodiment of the present invention. The device specifically comprises: a predicted meteorological data determination module 310, a total fuel consumption attribute determination module 320 and a navigation speed optimization module 330.

[0108] Among them, the predicted meteorological data determination module 310 is used to determine at least one group of predicted meteorological data according to the navigation data of the target ship; the total fuel consumption attribute determination module 320 is used to determine the total fuel consumption attribute corresponding to the target ship in each speed group according to the at least one group of predicted meteorological data, the draft data of the target ship and at least one speed group; wherein the at least one speed group includes multiple speeds, and the speeds in the same time slice are the same, and the time slice is divided according to the navigation data of the target ship; the navigation speed optimization module 330 is used to determine the target speed group from the at least one speed group according to the total fuel consumption attribute, so as to control the navigation speed of the target ship according to the speed in the target speed group.

[0109] The technical solution provided by the embodiment of the present invention can determine at least one set of predicted meteorological data that matches the navigation data by analyzing the acquired navigation data of the target ship. Next, the total fuel consumption attribute corresponding to the target ship under each speed group can be determined by analyzing and processing the at least one set of predicted meteorological data, the draft data of the target ship, and the generated at least one speed group. According to the total fuel consumption attribute and the fuel consumption and speed in the pre-set time charter contract, a target speed group can be determined from at least one speed group to control the travel of the target ship based on the target speed group, so as to achieve the effect of optimizing the navigation data under the conditions of the time charter contract.

[0110] On the basis of the above technical solution, the device further comprises:

[0111] A time slice determination module, used to determine at least one time slice according to the navigation time in the navigation data;

[0112] A speed determination module is used to determine the speed corresponding to each time slice according to a covariance optimization algorithm;

[0113] A first speed group determination module, used to determine a speed group according to the speed corresponding to each time slice;

[0114] The second speed group determination module is used to continuously use the covariance optimization algorithm to update the speed corresponding to each time slice to obtain multiple speed groups.

[0115] On the basis of the above technical solutions, the forecast meteorological data determination module includes:

[0116] A dimensional data determination unit is used to determine at least one time point and the longitude and latitude data corresponding to the time point according to the estimated departure time and the estimated arrival time in the navigation data; a predicted meteorological data determination unit is used to determine the predicted meteorological data for each time point according to the longitude and latitude data of the at least one time point; wherein the predicted meteorological data includes at least one of wind speed, wind direction, wave height, wave direction and water flow rate.

[0117] Based on the above technical solutions, the total fuel consumption attribute determination module includes:

[0118] A data prediction unit is used to input the speed group, the predicted meteorological data and the draft data into a pre-trained speed and fuel consumption prediction model for at least one speed group, so as to output the fuel consumption and speed corresponding to the target ship under the speed group at each time slice; a total fuel consumption attribute determination unit is used to determine the total fuel consumption attribute of the target ship when the fuel consumption and the speed meet preset constraints.

[0119] On the basis of the above technical solution, the preset constraints include:

[0120] The fuel consumption satisfies a preset fuel consumption constraint condition;

[0121] When the predicted meteorological data meets the preset meteorological constraint condition, the navigation speed meets the preset navigation speed threshold;

[0122] The mileage of the target ship reaches a preset mileage constraint within a preset time period.

[0123] On the basis of the above technical solutions, the navigation speed optimization module is further used to use the minimum total fuel consumption attribute as the target total fuel consumption attribute, and use the speed group corresponding to the target total fuel consumption attribute as the target speed group.

[0124] On the basis of the above technical solutions, the device further includes:

[0125] A data updating module is used to adjust the estimated arrival time in the navigation data if the target speed group is not determined, so as to determine the predicted meteorological data and the speed group at each time point based on the updated estimated arrival time; a speed group re-determination module is used to determine the target speed group corresponding to the target ship based on the updated predicted meteorological data and the updated speed group.

[0126] The speed optimization device applied to a ship provided by an embodiment of the present invention can execute the speed optimization method applied to a ship provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the speed optimization method applied to a ship.

[0127] It is worth noting that in the above-mentioned embodiment of the speed optimization device applied to ships, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0128] Figure 4 A schematic diagram of the structure of a server provided in an embodiment of the present invention. Figure 4 A block diagram of an exemplary server 12 suitable for use in implementing embodiments of the present invention is shown. Figure 4 The server 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0129] like Figure 4 As shown, the server 12 is in the form of a general purpose computing device. The components of the server 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0130] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0131] The server 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the server 12, including volatile and non-volatile media, removable and non-removable media.

[0132] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The server 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 4 not shown, usually called a "hard drive"). Although Figure 4 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0133] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0134] The server 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), may communicate with one or more devices that enable a user to interact with the server 12, and / or may communicate with any device that enables the server 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. In addition, the server 12 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with other modules of the server 12 via a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the server 12, including, but not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0135] The processing unit 16 executes various functional applications and data processing by running the program stored in the system memory 28, for example, implementing the steps of the speed optimization method applied to a ship provided in the first embodiment of the present invention, the method comprising:

[0136] Determine at least one set of forecast meteorological data according to the navigation data of the target ship;

[0137] Determine the total fuel consumption attribute corresponding to the target ship in each speed group according to the at least one set of predicted meteorological data, the draft data of the target ship, and at least one speed group; wherein the at least one speed group includes multiple speeds, and the speeds in the same time slice are the same, and the time slice is divided according to the navigation data of the target ship;

[0138] According to the total fuel consumption attribute, a target speed group is determined from the at least one speed group, so as to control the sailing speed of the target ship according to the speed in the target speed group.

[0139] Of course, those skilled in the art can understand that the processor can also implement the technical solution of the speed optimization method applied to a ship provided by any embodiment of the present invention.

[0140] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the method steps for optimizing the speed of a ship provided in the above embodiment of the present invention are implemented. The method includes:

[0141] Determine at least one set of forecast meteorological data according to the navigation data of the target ship;

[0142] Determine the total fuel consumption attribute corresponding to the target ship in each speed group according to the at least one set of predicted meteorological data, the draft data of the target ship, and at least one speed group; wherein the at least one speed group includes multiple speeds, and the speeds in the same time slice are the same, and the time slice is divided according to the navigation data of the target ship;

[0143] According to the total fuel consumption attribute, a target speed group is determined from the at least one speed group, so as to control the sailing speed of the target ship according to the speed in the target speed group.

[0144] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0145] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0146] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0147] Computer program code for performing the operation of embodiments of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0148] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A speed optimization method applied to a ship, characterized in that: include: Determine at least one set of forecast meteorological data according to the navigation data of the target ship; Determine the total fuel consumption attribute corresponding to the target ship in each speed group according to the at least one set of predicted meteorological data, the draft data of the target ship, and at least one speed group; wherein the at least one speed group includes multiple speeds, and the speeds in the same time slice are the same, and the time slice is divided according to the navigation data of the target ship; According to the total fuel consumption attribute, a target speed group is determined from the at least one speed group, so as to control the sailing speed of the target ship according to the speed in the target speed group.

2. The method according to claim 1, characterized in that: The method further comprises: Determining at least one time slice according to the navigation time in the navigation data; Determine the speed corresponding to each time slice based on the covariance optimization algorithm; According to the speed corresponding to each time slice, a speed group is determined; The covariance optimization algorithm is continuously used to update the rotation speed corresponding to each time slice to obtain multiple rotation speed groups.

3. The method according to claim 1, characterized in that The step of determining at least one set of forecast meteorological data based on the navigation data of the target ship comprises: Determine at least one time point and the longitude and latitude data corresponding to the time point according to the estimated departure time and the estimated arrival time in the navigation data; Determining the forecasted meteorological data for each time point based on the latitude and longitude data of the at least one time point; The predicted meteorological data includes at least one of wind speed, wind direction, wave height, wave direction and water flow rate.

4. The method according to claim 1, characterized in that: The determining, based on the at least one set of predicted meteorological data, the draft data of the target ship, and at least one speed group, a total fuel consumption attribute corresponding to the target ship in each speed group includes: For the at least one speed group, the speed group, the predicted meteorological data and the draft data are input into a pre-trained speed and fuel consumption prediction model to output the fuel consumption and speed corresponding to the target ship in each time slice under the speed group; When the fuel consumption and the rotation speed meet preset constraints, a total fuel consumption attribute of the target ship is determined.

5. The method according to claim 4, characterized in that The preset constraints include: The fuel consumption satisfies a preset fuel consumption constraint condition; When the predicted meteorological data meets the preset meteorological constraint condition, the navigation speed meets the preset navigation speed threshold; The mileage of the target ship reaches a preset mileage constraint within a preset time period.

6. The method according to claim 1, characterized in that Determining a target speed group from the at least one speed group according to the total fuel consumption attribute includes: The minimum total fuel consumption attribute is used as the target total fuel consumption attribute, and the speed group corresponding to the target total fuel consumption attribute is used as the target speed group.

7. The method according to claim 1, characterized in that The method further comprises: If the target speed group is not determined, adjusting the estimated arrival time in the navigation data to determine the predicted weather data and the speed group at each time point based on the updated estimated arrival time; The step of determining a target speed group corresponding to the target ship based on the updated predicted meteorological data and the updated speed group.

8. A server, characterized in that: The server includes: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the speed optimization method applied to a ship as described in any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the speed optimization method applied to a ship as described in any one of claims 1 to 7 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the speed optimization method applied to a ship as described in any one of claims 1 to 7 is implemented.

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