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Ship speed prediction and safety speed control method based on big data mining

A technology of safe speed and control method, applied in prediction, data processing application, ship traffic control and other directions, to achieve the effect of strong engineering practicability, small relative error of prediction, and high application and promotion value

Pending Publication Date: 2021-11-30
HOHAI UNIV
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] Ship navigation control is not only related to water flow, ship's own performance, and cargo loading, but also to complex factors such as the driver's own conditions and weather. It is difficult for the traditional theoretical calculation method of ship communication characteristics to fully consider these comprehensive factors. Intelligent algorithms under the background of big data can effectively reveal the influence of complex factors, so the use of intelligent algorithms and big data technology has become a hot frontier technology in the study of ship traffic characteristics

Method used

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  • Ship speed prediction and safety speed control method based on big data mining
  • Ship speed prediction and safety speed control method based on big data mining
  • Ship speed prediction and safety speed control method based on big data mining

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Embodiment 1

[0034] Such as figure 1 As shown, the ship traffic feature prediction and safe speed control method based on big data mining of the present embodiment includes the following steps:

[0035] (1) According to the main factors affecting ship navigation in plain river network channels, a large number of data samples are collected, taking into account the characteristics of drivers, and at the same time collecting ship speed, acceleration, gross tonnage, actual tonnage, ship age, driver's age, The data samples of the driver's driving age and bow distance are used to establish a sample database with multiple influencing factors; Table 1 shows some sample data of the collection database during the following process of 7 ships.

[0036] Table 1

[0037]

[0038] The data samples of 5 ships are selected from the sample database as the training sample set, and the data of the other ship is used as the prediction sample set.

[0039] (2) Using the fully connected deep learning neura...

Embodiment 2

[0072] This embodiment is the same as the method in Embodiment 1, the difference is that the present embodiment takes the bow distance as the prediction target, and obtains the multi-factor ship bow distance prediction model based on the genetic programming method as follows, and the ship bow distance under high multi-factor Predict "explicit" binary tree models such as Figure 7 Shown:

[0073]

[0074] In the formula:

[0075] x 7 : ship speed; x 1 : acceleration; x 2 : gross tonnage; x 3 : Actual load tonnage

[0076] x 4 : ship age; x 5 : age of the driver; x 6 : Driver's driving age; y 2 : Head pitch.

[0077] After the above model is obtained, the corresponding ship speed can be deduced according to the relationship between ship speed and bow distance by using the predicted head distance value.

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Abstract

The invention relates to a ship speed prediction and safe speed control method based on big data mining. The method comprises the following steps: firstly, collecting a sample database of multiple influence factors influencing ship navigation in a plain river network channel; then, constructing a full-connection deep learning neural network model, and optimizing initial parameters by taking prediction precision as a control target; by adopting the optimized full-connection deep learning neural network model, carrying out comparative analysis on the prediction precision of the multiple influence factors under different combinations, and selecting the combination of the optimal influence factors; on the basis of a data sample of the combination of the optimal influence factors, compiling a genetic programming algorithm program by adopting Python, optimizing core parameters by taking prediction precision as a target, and obtaining a parameter combination with the optimal precision; substituting the parameter combination with the optimal precision into an algorithm program to obtain a ship speed prediction model based on a genetic programming method; and finally, combining the ship speed obtained by the ship speed prediction model based on the genetic programming method with the risk coefficient to obtain the safety control ship speed.

Description

technical field [0001] The invention relates to a ship speed prediction and safe speed control method based on big data mining, and belongs to the technical field of ship traffic characteristics and traffic flow prediction. Background technique [0002] Ship navigation control is not only related to water flow, ship's own performance, and cargo loading, but also to complex factors such as the driver's own conditions and weather. It is difficult for the traditional theoretical calculation method of ship communication characteristics to fully consider these comprehensive factors. Intelligent algorithms under the background of big data can effectively reveal the influence rules of complex factors, so the use of intelligent algorithms and big data technology has become a hot frontier technology in the study of ship traffic characteristics. According to the actual situation, due to the effect of inertia when the ship is sailing, the faster the speed, the smaller the distance betw...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06N3/04G06N3/08
CPCG06Q10/04G06N3/08G06N3/086G06N3/045G06N3/04G08G3/00
Inventor 褚明生沈才华
Owner HOHAI UNIV
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