Method and system for predicting shipping and harbor arriving time of coal-fired transport ship

Abstract

The invention discloses a method and a system for predicting time of fire coal transportation ships to reach a port, and the method comprises the steps: analyzing historical navigation data of the fire coal transportation ships under the condition of non-meteorological factor delay, and determining characteristic parameters which affect the navigation time; constructing a prediction model based on the characteristic parameters and a preset neural network model to predict initial navigation prediction time; analyzing the meteorological data on the airline in a segmented manner, and determining the influence coefficient of the weather on each segment of the airline on the navigation time; performing comprehensive evaluation and calculation on navigation delay caused by weather on the whole course based on the influence coefficient on each course to obtain a weather delay evaluation value, and determining a weather delay coefficient based on the weather delay evaluation value; and compensating the initial navigation prediction time based on the meteorological delay coefficient to obtain the final navigation prediction time, and determining the dispatching harbor arrival time of the coal-fired transport ship based on the final navigation prediction time. According to the method, the shipping and harbor-arriving time of the ship can be accurately determined, so that harbor-arriving shipping of the ship can be reasonably arranged, and the shipping scheduling efficiency and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of predicting the arrival time of ships at ports, and particularly to a method and system for predicting the arrival time of coal transportation ships during dispatching and transportation. Background Art

[0002] As an important raw material for many industrial and energy enterprises, the efficient operation of the coal supply chain is crucial for the production and operation of related industries. As an important means of transportation for coal transportation, coal transportation ships play a crucial role in the global energy supply chain. Accurately predicting the arrival time of coal transportation ships during dispatching and transportation has a profound impact on the efficient operation of the supply chain and the economic benefits of shipping companies.

[0003] However, traditional methods for predicting the arrival time of coal transportation ships during dispatching and transportation usually fail to fully consider the impact of meteorological factors on the sailing time, which leads to uncertainties and delays that may occur during actual sailing. In fact, the sailing of coal transportation ships is directly affected by meteorological conditions. Factors such as wind speed, wave height, and visibility have important impacts on the sailing speed, route selection, and ship stability of ships. Therefore, in order to more accurately predict the arrival time of coal transportation ships during dispatching and transportation, it is necessary to consider the impact of meteorological factors on the sailing time. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention provides a method and system for predicting the arrival time of coal transportation ships during dispatching and transportation, including: Obtaining historical sailing data of coal transportation ships under non-meteorological factor delays, and analyzing the historical sailing data to determine characteristic parameters affecting the sailing time; Constructing a sailing time prediction model for coal transportation ships based on the characteristic parameters and a preset neural network model, and making a prediction according to the sailing time prediction model to obtain an initial sailing prediction time of the coal transportation ship; Obtaining meteorological data on the route corresponding to the coal transportation ship, and performing a segmented analysis of the route based on the meteorological data to determine the influence coefficient of the meteorology on the sailing time for each segment of the route; Comprehensively evaluating and calculating the delay caused by meteorology for the entire route based on the influence coefficient for each segment of the route to obtain a meteorological delay evaluation value, and determining a meteorological delay coefficient based on the meteorological delay evaluation value; Compensating the initial sailing prediction time of the coal transportation ship based on the meteorological delay coefficient to obtain a final sailing prediction time, and determining the arrival time of the coal transportation ship during dispatching and transportation based on the final sailing prediction time.

[0005] Further, the obtaining historical sailing data of coal transportation ships under non-meteorological factor delays, and analyzing the historical sailing data to determine characteristic parameters affecting the sailing time, includes: Obtain the historical navigation data of coal - transporting ships under non - meteorological - factor delays, and determine the historical navigation time data from the historical navigation data; Divide the remaining historical navigation data into several parameter data groups according to different parameter types, and analyze the correlation between each parameter data group and the historical navigation time data; Determine the characteristic parameters affecting the navigation time as the parameters corresponding to the parameter data groups with a correlation higher than the preset correlation value.

[0006] Further, constructing a navigation time prediction model for coal - transporting ships based on the characteristic parameters and a preset neural network model, and making a prediction according to the navigation time prediction model to obtain the initial navigation prediction time of the coal - transporting ship, including: Construct a data set based on the characteristic parameters and the historical navigation time data, and input the data set into the preset neural network model to construct an initial navigation time prediction model; Divide the data set into a training set and a test set according to a certain proportion, and input the training set and the test set into the initial navigation time prediction model; Train and test the initial navigation time prediction model until the initial navigation time prediction model meets the preset convergence condition to obtain the navigation time prediction model; Obtain the real - time navigation data of the coal - transporting ship, and input the real - time navigation data into the navigation time prediction model, and make a prediction by the navigation time prediction model to obtain the initial navigation prediction time of the coal - transporting ship.

[0007] Further, obtaining the meteorological data of the route corresponding to the coal - transporting ship, and based on the meteorological data, performing a sectional analysis on the route to determine the influence coefficient of the meteorology on the navigation time for each section of the route, including: Obtain the meteorological data of the route corresponding to the coal - transporting ship, and analyze the meteorological data to determine different meteorological types; Divide the route into several sections according to the meteorological types, and determine the meteorological type data for each section of the route; Divide the meteorological type data for each section of the route into several meteorological parameter data groups according to the meteorological parameter types, and screen out the meteorological parameter data groups corresponding to the preset meteorological parameters from the several meteorological parameter data groups as the key meteorological parameter data groups; Perform a comprehensive analysis on the several key meteorological parameter data groups for each section of the route, and determine the influence coefficient of the meteorology on the navigation time for each section of the route according to the analysis results.

[0008] Further, performing a comprehensive analysis on the several key meteorological parameter data groups for each section of the route, and determining the influence coefficient of the meteorology on the navigation time for each section of the route, including: Plot the time - series curves for each group of key meteorological parameter data respectively, and obtain the meteorological parameter time - series curve graphs corresponding to each group of key meteorological parameter data respectively. Determine the variation amplitude and average value in the meteorological parameter time - series curve graph corresponding to each group of key meteorological parameter data, and determine the sub - influence coefficient of each group of key meteorological parameter data based on the variation amplitude and average value. The calculation formula for the sub - influence coefficient is: ai = α * fi+β * pi, where ai is the sub - influence coefficient of the i - th group of key meteorological parameter data, α is the first conversion coefficient, fi is the variation amplitude of the i - th group of key meteorological parameter data, β is the second conversion coefficient, and pi is the average value of the i - th group of key meteorological parameter data. Based on the sub - influence coefficients of each key meteorological parameter on the sailing time and the preset weights of each key meteorological parameter on each section of the route, determine the influence coefficient of the meteorology on the sailing time on each section of the route. The calculation formula for the influence coefficient is: , where Ai is the influence coefficient of the meteorology on the sailing time on the i - th section of the route, li is the preset weight of the i - th group of key meteorological parameter data, ai is the sub - influence coefficient of the i - th group of key meteorological parameter data, and n is the number of groups of key meteorological parameter data.

[0009] Furthermore, comprehensively evaluate and calculate the meteorological - caused sailing delays on the entire section of the route based on the influence coefficients on each section of the route to obtain the meteorological delay evaluation value, including: Obtain the influence coefficients on each section of the route, and evaluate and obtain the influence evaluation value of each section of the route; Determine the length of each section of the route, and calculate the proportion of the length of each section of the route in the entire section of the route, and use this proportion as the weight of each section of the route; Perform weighted addition calculation on the influence evaluation value of each section of the route and the corresponding weight to obtain the meteorological delay evaluation value.

[0010] Furthermore, determining the meteorological delay coefficient based on the meteorological delay evaluation value includes: Preset the corresponding relationship between the meteorological delay coefficient - meteorological delay evaluation value intervals. For each meteorological delay evaluation value interval, a corresponding meteorological delay coefficient is associated; Obtain the meteorological delay evaluation value, and perform mapping within the corresponding relationship between the meteorological delay coefficient - meteorological delay evaluation value intervals based on the meteorological delay evaluation value interval to which the meteorological delay evaluation value belongs, and select the meteorological delay coefficient corresponding to the meteorological delay evaluation value interval.

[0011] Further, compensating the initial predicted sailing time of the coal - fired transportation ship based on the meteorological delay coefficient to obtain the final predicted sailing time, and determining the arrival time of the coal - fired transportation ship for transfer based on the final predicted sailing time, includes: Multiply the meteorological delay coefficient by the initial predicted sailing time of the coal - fired transportation ship to complete the compensation for the initial predicted sailing time, and obtain the final predicted sailing time of the coal - fired transportation ship; Obtain the departure time of the coal - fired transportation ship, and add the departure time to the final predicted sailing time to obtain the arrival time of the coal - fired transportation ship for transfer.

[0012] The present invention also provides a prediction system for the arrival time of a coal - fired transportation ship for transfer, including: An acquisition module, configured to acquire the historical sailing data of the coal - fired transportation ship under non - meteorological factor delays, and analyze the historical sailing data to determine the characteristic parameters affecting the sailing time; A prediction module, configured to construct a sailing time prediction model of the coal - fired transportation ship based on the characteristic parameters and a preset neural network model, and perform prediction according to the sailing time prediction model to obtain the initial predicted sailing time of the coal - fired transportation ship; An analysis module, configured to acquire the meteorological data of the route corresponding to the coal - fired transportation ship, and perform segmented analysis on the route based on the meteorological data to determine the influence coefficient of the meteorology on the sailing time for each section of the route; An evaluation module, configured to comprehensively evaluate and calculate the delay caused by meteorology for the entire route based on the influence coefficients for each section of the route to obtain a meteorological delay evaluation value, and determine the meteorological delay coefficient based on the meteorological delay evaluation value; A determination module, configured to compensate the initial predicted sailing time of the coal - fired transportation ship based on the meteorological delay coefficient to obtain the final predicted sailing time, and determine the arrival time of the coal - fired transportation ship for transfer based on the final predicted sailing time.

[0013] Compared with the prior art, the beneficial effects of a method and system for predicting the arrival time of a coal - fired transportation ship for transfer in an embodiment of the present invention are as follows: By combining non - meteorological factors and meteorological factors, the present invention analyzes the influence of meteorology on the sailing time, predicts and compensates the predicted sailing time according to this influence, and finally accurately determines the arrival time of the coal - fired transportation ship for transfer, thereby reasonably arranging the arrival and transfer of the ship, which helps to improve the efficiency and accuracy of shipping scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a schematic flow - chart structure diagram of a method for predicting the arrival time of a coal - fired transportation ship for transfer in an embodiment of the present invention; Figure 2It is a schematic diagram of a component of the arrival time prediction system for coal - fired transportation ships in the embodiments of the present invention. Detailed implementation manners

[0015] Combined with the accompanying drawings and embodiments, the detailed implementation manners of the present application will be further described in detail. The following embodiments are used to illustrate the present invention, but are not used to limit the scope of the present invention.

[0016] In the description of the present application, it should be understood that the orientation or positional relationship indicated by terms such as "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings. It is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the platform or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present application.

[0017] Terms "first", "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first", "second" may explicitly or implicitly include one or more of such features. In the description of the present application, unless otherwise stated, the meaning of "a plurality" is two or more.

[0018] In the description of the present application, it should be noted that unless otherwise clearly specified and limited, the terms "installed", "connected", "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific situations.

[0019] Such as Figure 1As shown in the figure, in the embodiment of the present application, a method for predicting the arrival time of a coal transportation ship is provided, including: S100: Obtain the historical navigation data of the coal transportation ship under non-meteorological factor delays, and analyze the historical navigation data to determine the characteristic parameters affecting the navigation time; S200: Based on the characteristic parameters and a preset neural network model, construct a navigation time prediction model for the coal transportation ship, and perform predictions according to the navigation time prediction model to obtain the initial navigation prediction time of the coal transportation ship; S300: Obtain the meteorological data on the route corresponding to the coal transportation ship, and based on the meteorological data, perform segmented analysis on the route to determine the influence coefficient of the meteorology on the navigation time for each section of the route; S400: Based on the influence coefficient for each section of the route, comprehensively evaluate and calculate the delay caused by the meteorology for the entire route to obtain a meteorological delay evaluation value, and determine a meteorological delay coefficient based on the meteorological delay evaluation value; S500: Compensate the initial navigation prediction time of the coal transportation ship based on the meteorological delay coefficient to obtain the final navigation prediction time, and determine the arrival time of the coal transportation ship for transfer based on the final navigation prediction time.

[0020] Further, the present invention combines non-meteorological factors and meteorological factors to analyze the influence of meteorology on the navigation time, and predicts and compensates the navigation prediction time according to this influence, and finally accurately determines the arrival time of the coal transportation ship for transfer, so as to reasonably arrange the arrival and transfer of the ship, which helps to improve the efficiency and accuracy of shipping scheduling.

[0021] In the embodiment of the present application, a method for predicting the arrival time of a coal transportation ship is provided. The obtaining of the historical navigation data of the coal transportation ship under non-meteorological factor delays and the analysis of the historical navigation data to determine the characteristic parameters affecting the navigation time include: obtaining the historical navigation data of the coal transportation ship under non-meteorological factor delays, and determining the historical navigation time data from the historical navigation data; dividing the remaining historical navigation data into several parameter data groups according to different parameter types, and analyzing the correlation between each parameter data group and the historical navigation time data; determining the parameters corresponding to the parameter data groups with a correlation higher than the preset correlation value as the characteristic parameters affecting the navigation time.

[0022] Specifically, obtain the historical navigation data of coal - transporting ships under non - meteorological - factor delays, including navigation time data and non - meteorological - factor data that may affect navigation time, such as ship load, route length, ship type, ship status (such as whether maintenance is being carried out), waterway congestion, etc.; divide these historical navigation data into several parameter data groups according to different parameter types, such as ship - related data groups, route - related data groups, ship - status - related data groups, etc.; through data - analysis methods, such as correlation analysis, regression analysis, etc., analyze the correlation between each parameter data group and the historical navigation time data. During the analysis process, a preset correlation value is set in advance as a threshold, and the parameter data groups with values higher than this value can be determined as characteristic parameters affecting navigation time. This step determines the characteristic parameters affecting navigation time through in - depth analysis of historical navigation data, thereby enabling the targeted establishment of a prediction model. Such a prediction model can more accurately consider the impact of non - meteorological factors on navigation time, improve the accuracy and reliability of prediction. Through the analysis of characteristic parameters, shipping companies can better optimize ship dispatching plans, reduce delay risks, and improve transportation efficiency, thus providing more reliable support for the sustainable development and operational efficiency of the shipping industry.

[0023] In an embodiment of the present application, a method for predicting the arrival time of coal - transporting ships is provided. A navigation - time prediction model for coal - transporting ships is constructed based on characteristic parameters and a preset neural network model, and prediction is carried out according to the navigation - time prediction model to obtain the initial navigation prediction time of coal - transporting ships, including: constructing a data set based on characteristic parameters and historical navigation time data, and inputting the data set into the preset neural network model to construct an initial navigation - time prediction model; dividing the data set into a training set and a test set according to a certain ratio, and inputting the training set and the test set into the initial navigation - time prediction model; training and testing the initial navigation - time prediction model until the initial navigation - time prediction model meets the preset convergence condition to obtain the navigation - time prediction model; obtaining the real - time navigation data of coal - transporting ships, and inputting the real - time navigation data into the navigation - time prediction model, and the navigation - time prediction model performs prediction to obtain the initial navigation prediction time of coal - transporting ships.

[0024] Specifically, a dataset is constructed based on the characteristic parameters and historical sailing time data. The characteristic parameters are used as input features, and the historical sailing time data is used as output labels to construct a training dataset. The constructed dataset is divided into a training set and a test set according to a certain ratio. The training set is used to train the neural network model, and the test set is used to evaluate the performance of the model. The training set and the test set are input into a preset neural network model for model training and testing. During the training process, the neural network model will gradually adjust its own parameters to minimize the error between the predicted value and the true value. The training process will continue until the model meets the preset convergence condition, that is, the performance of the model reaches an acceptable level. When real-time sailing data is obtained, these data can be input into the trained sailing time prediction model, and the model will make a prediction based on the input real-time data to obtain the initial sailing prediction time of the coal transportation ship. Through the training and testing of the neural network model in this step, a model that can predict the sailing time of the coal transportation ship is obtained. This model can consider the influence of various characteristic parameters on the sailing time, improve the accuracy and reliability of the prediction. By inputting real-time sailing data, the model can predict the sailing time of the coal transportation ship in a timely and accurate manner, helping the shipping company better arrange the transportation plan of the ship, improve transportation efficiency, reduce costs, and improve customer satisfaction.

[0025] In an embodiment of the present application, a method for predicting the arrival time of a coal transportation ship at the port is provided. Obtaining the meteorological data of the route corresponding to the coal transportation ship, and based on the meteorological data, segmentally analyzing the route to determine the influence coefficient of the meteorology on the sailing time for each section of the route, including: obtaining the meteorological data of the route corresponding to the coal transportation ship, and analyzing the meteorological data to determine different meteorological types; dividing the route into several sections according to the meteorological types, and determining the meteorological type data for each section of the route; dividing the meteorological type data for each section of the route into several meteorological parameter data groups according to the meteorological parameter types, and screening out the meteorological parameter data groups corresponding to the preset meteorological parameters from the several meteorological parameter data groups as the key meteorological parameter data groups; comprehensively analyzing the several key meteorological parameter data groups for each section of the route, and determining the influence coefficient of the meteorology on the sailing time for each section of the route according to the analysis results.

[0026] Specifically, obtaining the meteorological data of the coal transportation ships on the corresponding shipping routes is to consider the impact of meteorological factors on the sailing time. Analyzing the meteorological data to determine different meteorological types can help us understand the characteristics and challenges of ship sailing under different meteorological conditions. Dividing the shipping route into several segments according to the meteorological types and determining the meteorological type data of each segment of the shipping route can help us better understand the changes in meteorological conditions on the shipping route and provide basic data for subsequent analysis. Dividing the meteorological type data of each segment of the shipping route into several meteorological parameter data groups according to the meteorological parameter types, and screening out the meteorological parameter data groups corresponding to the preset meteorological parameters as the key meteorological parameter data groups. These key meteorological parameter data groups may be meteorological parameters that have a significant impact on the sailing time, such as strong winds and large waves. Conducting a comprehensive analysis of the several key meteorological parameter data groups on each segment of the shipping route and determining the influence coefficient of the meteorology on the sailing time for each segment of the shipping route based on the analysis results. Such analysis can determine the variation law of the sailing time under different meteorological conditions and provide an important reference basis for establishing a sailing time prediction model in the future. This step fully considers the impact of meteorological factors on the sailing time and determines the influence coefficient of different meteorological conditions on the sailing time through a comprehensive analysis of the meteorological data on the shipping route.

[0027] In the embodiment of the present application, a method for predicting the arrival time of coal transportation ships is provided. The comprehensive analysis of several key meteorological parameter data groups on each segment of the shipping route and determining the influence coefficient of the meteorology on the sailing time for each segment of the shipping route includes: respectively plotting each key meteorological parameter data group as a time series curve to obtain the meteorological parameter time series curve diagram corresponding to each key meteorological parameter data group; determining the change range and average value in the meteorological parameter time series curve diagram corresponding to each key meteorological parameter data group, and determining the sub-influence coefficient of each key meteorological parameter data group based on the change range and average value. The calculation formula of the sub-influence coefficient is: ai = α * fi + β * pi, where ai is the sub-influence coefficient of the i-th key meteorological parameter data group, α is the first conversion coefficient, fi is the change range of the i-th key meteorological parameter data group, β is the second conversion coefficient, and pi is the average value of the i-th key meteorological parameter data group; determining the influence coefficient of the meteorology on the sailing time for each segment of the shipping route based on the sub-influence coefficients of each key meteorological parameter on the sailing time and the preset weights of each key meteorological parameter on each segment of the shipping route. The calculation formula of the influence coefficient is: , Among them, \(A_i\) is the influence coefficient of the meteorology on the sailing time on the \(i\)-th section of the shipping route, \(l_i\) is the preset weight of the \(i\)-th key meteorological parameter data group, \(a_i\) is the sub-influence coefficient of the \(i\)-th key meteorological parameter data group, and \(n\) is the number of key meteorological parameter data groups.

[0028] Specifically, each key meteorological parameter data group is plotted as a time series curve, which can intuitively show the change of meteorological parameters over time. Through these curve graphs, the fluctuations and trends of different meteorological parameters over time can be observed; the change range and average value in the time series curve graph of the meteorological parameter corresponding to each key meteorological parameter data group are determined. The change range can reflect the fluctuation degree of the meteorological parameter, while the average value represents the average level of the meteorological parameter; the sub-influence coefficient of each key meteorological parameter data group is determined based on the change range and average value. By converting the change range and average value into sub-influence coefficients, the influence degree of each key meteorological parameter on the sailing time is quantified; based on the sub-influence coefficients of each key meteorological parameter on the sailing time and the preset weights of each key meteorological parameter on each section of the shipping route, the influence coefficient of the meteorology on the sailing time on each section of the shipping route is determined, and the influence of each key meteorological parameter can be comprehensively considered, and the influence coefficient of the meteorology on the sailing time on each section of the shipping route can be calculated. This step quantifies the influence degree of meteorological factors on the sailing time through time series analysis and influence coefficient calculation of meteorological parameters, which can help shipping companies better understand the influence law of meteorology on the sailing time and provide a more accurate reference basis for ship sailing plans.

[0029] In the embodiment of the present application, a method for predicting the arrival time of a coal transportation ship is provided. The comprehensive evaluation and calculation of the delay caused by meteorology on the entire shipping route based on the influence coefficient on each section of the shipping route to obtain a meteorological delay evaluation value includes: obtaining the influence coefficient on each section of the shipping route and evaluating and taking values for the influence coefficient to obtain the influence evaluation value of each section of the shipping route; determining the length of each section of the shipping route and calculating the ratio of the length of each section of the shipping route to the entire shipping route, and taking this ratio as the weight of each section of the shipping route; performing weighted addition calculation on the influence evaluation value of each section of the shipping route and the corresponding weight to obtain the meteorological delay evaluation value.

[0030] Specifically, obtain the influence coefficient for each route segment, evaluate and assign values to this influence coefficient to obtain the influence evaluation value for each route segment, comprehensively evaluate the meteorological influence coefficient for each route segment to understand the overall influence degree of meteorology on the route; determine the length of each route segment, calculate the proportion of the length of each route segment in the entire route, and use this proportion as the weight for each route segment. The weight can help consider the different degrees of meteorological influence caused by different route lengths in the comprehensive evaluation; perform weighted addition calculation on the influence evaluation value of each route segment and the corresponding weight to obtain the meteorological delay evaluation value. By comprehensively considering the meteorological influence degree of each route segment and the trade-off of the route length on the influence degree, the meteorological delay evaluation value is obtained. This value can be used to evaluate the delay situation of the route under different meteorological conditions. This step obtains the meteorological delay evaluation value by comprehensively evaluating the influence coefficient of each route segment and considering the weight of the route length on the influence, which can help shipping companies more comprehensively understand the influence degree of meteorology on the route and provide important references for voyage planning and scheduling.

[0031] In an embodiment of the present application, a method for predicting the arrival time of a coal transportation ship at the port is provided. Determining the meteorological delay coefficient based on the meteorological delay evaluation value includes: presetting the correspondence between the meteorological delay coefficient - meteorological delay evaluation value intervals. For each meteorological delay evaluation value interval in the correspondence between the meteorological delay coefficient - meteorological delay evaluation value intervals, a corresponding meteorological delay coefficient is associated; obtain the meteorological delay evaluation value, and perform mapping within the correspondence between the meteorological delay coefficient - meteorological delay evaluation value intervals based on the meteorological delay evaluation value interval to which the meteorological delay evaluation value belongs, and select the meteorological delay coefficient corresponding to the meteorological delay evaluation value interval.

[0032] Specifically, preset the correspondence between the meteorological delay coefficient - meteorological delay evaluation value intervals, that is, preset the corresponding meteorological delay coefficients for different ranges of meteorological delay evaluation values. Such a preset correspondence can help map the meteorological delay evaluation value to a specific meteorological delay coefficient to better understand the delay influence of meteorology on the route; obtain the meteorological delay evaluation value, and perform mapping within the correspondence between the meteorological delay coefficient - meteorological delay evaluation value intervals based on the meteorological delay evaluation value interval to which the meteorological delay evaluation value belongs. According to the actual meteorological delay evaluation value, find the interval to which it belongs and select the meteorological delay coefficient corresponding to that interval. This step pre - establishes the mapping relationship between the meteorological delay evaluation value and the meteorological delay coefficient, and can obtain the corresponding meteorological delay coefficient according to the actual meteorological delay evaluation value, helping shipping companies more intuitively understand the delay influence degree of meteorology on the route and providing important references for risk assessment and decision - making.

[0033] In an embodiment of the present application, a method for predicting the arrival time of a coal - transporting ship during transfer is provided. The method compensates the initial predicted sailing time of the coal - transporting ship based on a meteorological delay coefficient to obtain the final predicted sailing time, and determines the arrival time of the coal - transporting ship during transfer based on the final predicted sailing time, including: multiplying the meteorological delay coefficient by the initial predicted sailing time of the coal - transporting ship to complete the compensation of the initial predicted sailing time and obtain the final predicted sailing time of the coal - transporting ship; obtaining the departure time of the coal - transporting ship, and adding the departure time to the final predicted sailing time to obtain the arrival time of the coal - transporting ship during transfer.

[0034] Specifically, multiplying the meteorological delay coefficient by the initial predicted sailing time of the coal - transporting ship adjusts the initial predicted time according to the meteorological delay coefficient, taking into account the impact of meteorological factors on the sailing time, so as to obtain the final predicted sailing time after meteorological delay adjustment; obtaining the departure time of the coal - transporting ship, and adding the departure time to the final predicted sailing time to obtain the arrival time of the coal - transporting ship during transfer. By adding the departure time to the predicted sailing time, the expected arrival time of the coal - transporting ship can be obtained, taking into account the impact of meteorological delay factors on the sailing time. This step compensates the initial predicted sailing time of the ship using the meteorological delay coefficient, taking into account the impact of meteorological factors on the sailing time, thus obtaining a more accurate final predicted sailing time. At the same time, calculating the arrival time of the coal - transporting ship during transfer can also help shipping companies better arrange the scheduling and transportation plans of the ships, taking into account the actual impact of meteorological factors on ship transportation, and improving the accuracy and reliability of the transportation plan.

[0035] Such as Figure 2As shown in the figure, in an embodiment of the present application, a prediction system for the arrival time of a coal - transporting ship during transfer is provided, including: an acquisition module, configured to acquire the historical navigation data of the coal - transporting ship under non - meteorological - factor delays, analyze the historical navigation data, and determine the characteristic parameters affecting the navigation time; a prediction module, configured to construct a navigation - time prediction model for the coal - transporting ship based on the characteristic parameters and a preset neural network model, and perform a prediction according to the navigation - time prediction model to obtain the initial navigation prediction time of the coal - transporting ship; an analysis module, configured to acquire the meteorological data of the route corresponding to the coal - transporting ship, and perform a segmented analysis of the route based on the meteorological data to determine the influence coefficient of the meteorology on each section of the route on the navigation time; an evaluation module, configured to comprehensively evaluate and calculate the navigation delay caused by meteorology on the entire route based on the influence coefficient of each section of the route, obtain a meteorological - delay evaluation value, and determine a meteorological - delay coefficient based on the meteorological - delay evaluation value; a determination module, configured to compensate the initial navigation prediction time of the coal - transporting ship based on the meteorological - delay coefficient to obtain the final navigation prediction time, and determine the arrival time of the coal - transporting ship during transfer based on the final navigation prediction time.

[0036] In summary, the embodiment of the present invention provides a method and system for predicting the arrival time of a coal - transporting ship during transfer, which includes: analyzing the historical navigation data of the coal - transporting ship under non - meteorological - factor delays to determine the characteristic parameters affecting the navigation time; constructing a prediction model based on the characteristic parameters and a preset neural network model to predict the initial navigation prediction time; segmentally analyzing the meteorological data of the route to determine the influence coefficient of the meteorology on each section of the route on the navigation time; comprehensively evaluating and calculating the navigation delay caused by meteorology on the entire route based on the influence coefficient of each section of the route to obtain a meteorological - delay evaluation value, and determining a meteorological - delay coefficient based on it; compensating the initial navigation prediction time based on the meteorological - delay coefficient to obtain the final navigation prediction time, and determining the arrival time of the coal - transporting ship during transfer based on it. The present invention can accurately determine the arrival time of the ship during transfer, so as to reasonably arrange the arrival and transfer of the ship, improving the efficiency and accuracy of shipping scheduling.

[0037] Finally, it should be noted that: Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. In this case, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and its equivalent technologies, the present invention also intends to include these changes and modifications.

[0038] The above is only one embodiment of the present invention, but it should not be used to limit the scope of the present invention. Any structural changes made in accordance with the present invention, as long as they do not deviate from the essence of the present invention, should be regarded as falling within the protection scope of the present invention and being restricted. Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process and related descriptions of the above-described platform can refer to the corresponding processes in the foregoing platform embodiments and will not be repeated here.

[0039] The term "comprising" or any other similar term is intended to cover non-exclusive inclusion, such that a process, platform, article, or device / platform that comprises a series of elements includes not only those elements but also other elements not expressly listed, or also elements inherent to these process, platform, article, or device / platform.

[0040] So far, the technical solutions of the present invention have been described in combination with the further embodiments shown in the accompanying drawings. However, those skilled in the art can easily understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to closely related technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of the present invention.

[0041] The above is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. A method for predicting the arrival time of a coal - fired transportation ship at the port, characterized in that, Including: Obtain the historical navigation data of coal - fired transportation ships under non - meteorological factor delays, and analyze the historical navigation data to determine the characteristic parameters affecting the navigation time; Construct a navigation time prediction model for coal - fired transportation ships based on the characteristic parameters and a preset neural network model, and make a prediction according to the navigation time prediction model to obtain the initial navigation prediction time of the coal - fired transportation ships; Obtain the meteorological data of the route corresponding to the coal - fired transportation ships, and conduct a segmented analysis of the route based on the meteorological data to determine the influence coefficient of the meteorology on the navigation time for each section of the route; Based on the influence coefficients of each section of the route, comprehensively evaluate and calculate the navigation delays caused by meteorology for the entire section of the route to obtain a meteorological delay evaluation value, and determine a meteorological delay coefficient based on the meteorological delay evaluation value; Compensate the initial navigation prediction time of the coal - fired transportation ships based on the meteorological delay coefficient to obtain the final navigation prediction time, and determine the arrival time of the coal - fired transportation ships for transfer based on the final navigation prediction time.

2. A method for predicting the arrival time of a coal - transporting ship at the port after being transferred, according to claim 1, wherein The obtaining of the historical navigation data of coal - fired transportation ships under non - meteorological factor delays, and the analysis of the historical navigation data to determine the characteristic parameters affecting the navigation time includes: Obtain the historical navigation data of coal - fired transportation ships under non - meteorological factor delays, and determine the historical navigation time data from the historical navigation data; Divide the remaining historical navigation data into several parameter data groups according to different parameter types, and analyze the correlation between each parameter data group and the historical navigation time data; Determine the parameters corresponding to the parameter data groups with a correlation higher than the preset correlation value as the characteristic parameters affecting the navigation time.

3. A method for predicting the arrival time of a coal - fired transportation ship upon arrival at the port according to claim 2, characterized in that, The constructing of a navigation time prediction model for coal - fired transportation ships based on the characteristic parameters and a preset neural network model, and the making of a prediction according to the navigation time prediction model to obtain the initial navigation prediction time of the coal - fired transportation ships includes: Construct a data set based on the characteristic parameters and the historical navigation time data, and input the data set into the preset neural network model to construct an initial navigation time prediction model; Divide the data set into a training set and a test set according to a certain proportion, and input the training set and the test set into the initial navigation time prediction model; Train and test the initial navigation time prediction model until the initial navigation time prediction model meets the preset convergence condition to obtain the navigation time prediction model; Obtain the real - time navigation data of the coal - fired transportation ships, and input the real - time navigation data into the navigation time prediction model, and make a prediction by the navigation time prediction model to obtain the initial navigation prediction time of the coal - fired transportation ships.

4. A method for predicting the arrival time of a coal transportation ship at the port according to claim 3, characterized in that The obtaining of the meteorological data of the route corresponding to the coal - fired transportation ships, and the conducting of a segmented analysis of the route based on the meteorological data to determine the influence coefficient of the meteorology on the navigation time for each section of the route includes: Obtain the meteorological data of the route corresponding to the coal - fired transportation ships, and analyze the meteorological data to determine different meteorological types; Divide the route into several sections according to the meteorological types, and determine the meteorological type data for each section of the route; Divide the meteorological type data on each route segment into several meteorological parameter data groups according to the meteorological parameter type, and screen out the meteorological parameter data groups corresponding to the preset meteorological parameters from the several meteorological parameter data groups as the key meteorological parameter data groups; Conduct a comprehensive analysis of the several key meteorological parameter data groups on each route segment, and determine the influence coefficient of the meteorology on the sailing time on each route segment according to the analysis results.

5. A method for predicting the arrival time of a coal transportation ship at the port according to claim 4, characterized in that, The comprehensive analysis of the several key meteorological parameter data groups on each route segment and the determination of the influence coefficient of the meteorology on the sailing time on each route segment according to the analysis results include: Respectively plot each key meteorological parameter data group as a time series curve, and respectively obtain the meteorological parameter time series curve graph corresponding to each key meteorological parameter data group; Determine the change amplitude and average value in the meteorological parameter time series curve graph corresponding to each key meteorological parameter data group, and determine the sub-influence coefficient of each key meteorological parameter data group based on the change amplitude and average value. The calculation formula of the sub-influence coefficient is: ai = α * fi + β * pi, where ai is the sub-influence coefficient of the i-th key meteorological parameter data group, α is the first conversion coefficient, fi is the change amplitude of the i-th key meteorological parameter data group, β is the second conversion coefficient, and pi is the average value of the i-th key meteorological parameter data group; Based on the sub-influence coefficients of each key meteorological parameter on the sailing time on each route segment and the preset weights of each key meteorological parameter, determine the influence coefficient of the meteorology on the sailing time on each route segment. The calculation formula of the influence coefficient is: ， where Ai is the influence coefficient of the meteorology on the sailing time on the i-th route segment, li is the preset weight of the i-th key meteorological parameter data group, ai is the sub-influence coefficient of the i-th key meteorological parameter data group, and n is the number of key meteorological parameter data groups.

6. A method for predicting the arrival time of a coal transportation ship adjusted according to claim 4, wherein The comprehensive evaluation and calculation of the meteorological delay caused by the meteorology on the entire route segment based on the influence coefficient on each route segment to obtain the meteorological delay evaluation value include: Obtain the influence coefficient on each route segment, and conduct an evaluation and value-taking on the influence coefficient to obtain the influence evaluation value of each route segment; Determine the length of each route segment, and calculate the ratio of the length of each route segment to the entire route segment, and use this ratio as the weight of each route segment; Perform a weighted addition calculation on the influence evaluation value of each route segment and the corresponding weight to obtain the meteorological delay evaluation value.

7. A method for predicting the arrival time of a coal - transporting ship during transfer according to claim 6, characterized in that The determination of the meteorological delay coefficient based on the meteorological delay evaluation value includes: Preset the corresponding relationship between the meteorological delay coefficient - meteorological delay evaluation value interval. For each meteorological delay evaluation value interval, a corresponding meteorological delay coefficient is associated; Obtain the meteorological delay evaluation value, and map it within the corresponding relationship between the meteorological delay coefficient - meteorological delay evaluation value interval based on the meteorological delay evaluation value interval to which the meteorological delay evaluation value belongs, and select the meteorological delay coefficient corresponding to the meteorological delay evaluation value interval.

8. A method for predicting the arrival time of a coal transportation ship at the port according to claim 7, characterized in that, Compensating the initial voyage prediction time of the coal - fired transportation ship based on the meteorological delay coefficient to obtain the final voyage prediction time, and determining the transfer arrival time of the coal - fired transportation ship based on the final voyage prediction time, including: Multiplying the meteorological delay coefficient by the initial voyage prediction time of the coal - fired transportation ship to complete the compensation of the initial voyage prediction time and obtain the final voyage prediction time of the coal - fired transportation ship; Obtaining the departure time of the coal - fired transportation ship, and adding the departure time to the final voyage prediction time to obtain the transfer arrival time of the coal - fired transportation ship.

9. A prediction system for the arrival time of a coal - transporting ship, characterized in that, Including: An acquisition module, configured to acquire the historical voyage data of the coal - fired transportation ship under non - meteorological - factor delays, analyze the historical voyage data, and determine the characteristic parameters affecting the voyage time; A prediction module, configured to construct a voyage - time prediction model of the coal - fired transportation ship based on the characteristic parameters and a preset neural network model, and perform prediction according to the voyage - time prediction model to obtain the initial voyage prediction time of the coal - fired transportation ship; An analysis module, configured to acquire the meteorological data of the route corresponding to the coal - fired transportation ship, and perform sectional analysis on the route based on the meteorological data to determine the influence coefficient of the meteorology on the voyage time for each section of the route; An evaluation module, configured to comprehensively evaluate and calculate the delay caused by meteorology for the entire voyage based on the influence coefficients for each section of the route to obtain a meteorological delay evaluation value, and determine the meteorological delay coefficient based on the meteorological delay evaluation value; A determination module, configured to compensate the initial voyage prediction time of the coal - fired transportation ship based on the meteorological delay coefficient to obtain the final voyage prediction time, and determine the transfer arrival time of the coal - fired transportation ship based on the final voyage prediction time.

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