A Fuzzy Forecasting Method of Ship Short-term Traffic Flow Based on Chaos Theory

A short-term traffic flow, fuzzy prediction technology, applied in the direction of ship traffic control, traffic control system, instruments, etc., can solve the problems of large fluctuation of ship traffic flow, not in line with the actual situation of ship movement, etc., to improve the accuracy of prediction. Effect

Active Publication Date: 2021-06-25
江苏航运职业技术学院
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0005] Although ship traffic flow is affected by many uncertain factors, such as sea conditions, traffic accidents, economic situation, etc., there are fundamental factors that have been playing a leading role in the long-term trend of frequent fluctuations in ship traffic flow, that is to say , the change of ship traffic flow has a certain trend, and is affected by many uncertain factors, and this effect makes the ship traffic flow fluctuate greatly, which cannot be ignored
However, although some uncertain factors are also considered in the currently commonly used forecasting algorithms, they all give accurate predictions of ship traffic flow, which is not in line with the actual situation of ship movement, so the trend prediction of ship traffic flow is given is more reasonable

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  • A Fuzzy Forecasting Method of Ship Short-term Traffic Flow Based on Chaos Theory
  • A Fuzzy Forecasting Method of Ship Short-term Traffic Flow Based on Chaos Theory
  • A Fuzzy Forecasting Method of Ship Short-term Traffic Flow Based on Chaos Theory

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Embodiment 1

[0045] Such as figure 1 and figure 2 As shown, the present embodiment provides a fuzzy prediction method for short-term traffic flow of ships based on chaos theory, including the following steps:

[0046] S1. Construct a way of assigning navigation belts, divide the navigation belt into two sub-navigation belts with the opposite and equal navigation bandwidth through the navigation dividing line, and each sub-navigation belt is divided into three virtual navigation lanes; collect the MMSI of each ship Code and real-time latitude and longitude, channel speed difference, and occupancy rate AIS data, and make preprocessing analysis on the changing trend of traffic flow factors such as ship position, ship trajectory, ship direction and ship speed; The AIS data of the speed difference of different flight paths and the speed difference of different flight paths on different sub-airways, on the same flight path, the ratio of the maximum value of the cumulative time course of a cert...

Embodiment 2

[0061] This embodiment is an improvement made on the basis of the first embodiment, specifically as follows: the AIS data collection for the channel differential speed in step S1 in the first embodiment is expanded from the original two aspects to five aspects.

[0062] Specifically, the five types of AIS data that collect ship channel speed differences are: the channel speed difference of ships before and after the same channel; the channel speed difference of adjacent ships between adjacent channels; the speed difference of different sections of the same channel , especially the channel speed difference between the straight section and the curved section; the channel speed difference of different ship types, especially the navigation speed difference of ships with different tonnages; the maximum and minimum navigation speed differences of ships of the same tonnage on the same channel. Comparing the data of the two kinds of waterway differential speeds in the first embodiment,...

Embodiment 3

[0064] This embodiment also makes improvements on the basis of Embodiment 1, specifically as follows: In Embodiment 1, the waterway corresponding to the maximum occupancy rate of the ship on the navigation belt is used as the waterway for the ship to navigate;

[0065] Specifically, here we will mainly explain the situation that the maximum lane occupancy rate of the ship is different. If the maximum lane occupancy rate of the ship is 90%-100%, it means that the ship is traveling on the same channel and there is no cross-lane navigation; If the lane rate is 50% and below, it is determined that the ship must have continuous cross-lane navigation; if the maximum lane occupancy rate of the ship is between 50% and 90%, the ship may have a single cross-lane navigation or continuous cross-lane navigation .

[0066] Classify the ship's navigation according to the lane occupancy rate, so that you can clearly understand the true navigation route and direction of the ship, reduce the sa...

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Abstract

The invention discloses a fuzzy prediction method for short-term traffic flow of ships based on chaos theory, which includes: constructing the division mode of the navigation zone, collecting AIS data of MMSI code, real-time latitude and longitude, channel speed difference, and occupancy rate, and predicting Processing and analysis; use the wolf method to calculate the AIS data, determine the Lyapunov index of the ship traffic flow, and analyze the chaotic characteristics; use the takens theorem to realize the phase space reconstruction of the chaotic time series, and obtain the basis of forecasting data; compare different forecasting theories The model uses the support vector regression model (SVR) to predict; the algorithm of fuzzy structural elements is used to calculate the ambiguity function of the data points of the prediction results, and together with the predicted values, the fuzzy prediction results of the short-term ship traffic flow are constructed. In the present invention, the collection of AIS data of channel speed difference and lane occupancy rate, and the fuzzy prediction algorithm based on the fuzzy structural element method can comprehensively include the information characteristics of real ship traffic flow, and improve the accuracy of short-term ship prediction.

Description

technical field [0001] The invention relates to the technical field of ship traffic flow prediction, in particular to a fuzzy prediction method for short-term ship traffic flow based on chaos theory. Background technique [0002] With the continuous deepening of economic globalization and the deepening of trade cooperation among countries, the number of ships has also continued to increase, resulting in a rapid increase in ship traffic in many important waterways. Traffic flow is the best embodiment of the state of ship movement, the main reference for maximizing the benefits of water transportation facilities, formulating shipping development strategies, and rationally utilizing resources, and an important reference for the construction scale of water transportation facilities. By quantitatively or visually analyzing the traffic flow rules of ships in important voyages, it provides a powerful means and method for evaluating the passage capacity, organizational and managemen...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G3/00
CPCG08G3/00
Inventor 陈婷婷郭云龙芮乐军
Owner 江苏航运职业技术学院
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