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Traffic flow prediction method and system based on weighted fractional order grey model

A forecasting method and forecasting system technology, applied in the traffic control system of road vehicles, traffic control system, traffic flow detection, etc., can solve problems such as difficult to meet traffic information needs, achieve real-time forecasting ability and effect, improve accuracy and The effect of promoting generalization ability and improving prediction speed

Inactive Publication Date: 2020-10-09
NANTONG UNIVERSITY
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Problems solved by technology

Due to the high complexity, randomness and uncertainty of the operation of the traffic system, it is difficult to grasp the characteristics of the traffic flow only from the long-term scale to meet the needs of traffic management for traffic information.

Method used

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  • Traffic flow prediction method and system based on weighted fractional order grey model
  • Traffic flow prediction method and system based on weighted fractional order grey model
  • Traffic flow prediction method and system based on weighted fractional order grey model

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Embodiment Construction

[0031] refer to figure 1 , a traffic flow prediction method based on a weighted fractional gray model proposed by the present invention includes the following steps.

[0032] S1. Process the traffic flow data with a weighted fractional accumulation operator to obtain an accumulation generation sequence.

[0033] Specifically, in this step, the original sequence is first obtained through the traffic flow data; then the original sequence is generated by weighted fractional order accumulation.

[0034] In this embodiment, the original sequence is expressed as:

[0035] x (0) ={x (0) (1),x (0) (2),...,x (0) (t)} T ;

[0036] where x (0) (k) is traffic flow data, and x (0) (k)≥0, k=1, 2, . . . t.

[0037] In this embodiment, the model generated by performing weighted fractional accumulation on the original sequence is:

[0038]

[0039] Among them, X (rλ) Indicates the cumulative generation sequence, r and λ are calculation constants, and r, λ∈(0,1]; x (0) (i) is tr...

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Abstract

The invention provides a traffic flow prediction method based on a weighted fractional order gray model, and the method comprises the following steps: processing traffic flow data through a weighted fractional order accumulation operator to obtain an accumulation generation sequence; establishing a weighted fractional order grey prediction model according to the accumulation generation sequence; and predicting the traffic flow data by using the weighted fractional order grey prediction model. According to the method, the weighted fractional order grey prediction model does not need a large amount of data as a prediction basis, so that the calculation redundancy is reduced, the calculation difficulty is reduced, the prediction speed is increased, and the real-time prediction capability andeffect of the method on the traffic flow are ensured.

Description

technical field [0001] The invention relates to the technical field, in particular to a traffic flow prediction method and system based on a weighted fractional gray model. Background technique [0002] Intelligent Transportation System (Intelligent Transportation System, ITS) is an all-round comprehensive traffic management system that adopts advanced technology and integrates multiple functions. The system organically applies modern methods such as computer technology, data communication technology, sensor technology, and information technology to the entire transportation system, reasonably predicts road speed, traffic flow, density and other data, and provides information to travelers and traffic management. The department provides real-time, efficient, and accurate information, strengthens the connection among vehicles, roads, and users, and establishes an efficient integrated traffic management system. However, the road traffic system is a time-varying, complex nonlin...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01G08G1/065G06Q10/04G06Q10/06G06Q50/26G06N10/00
CPCG08G1/0125G08G1/0137G08G1/065G06Q10/04G06Q10/067G06Q50/26G06N10/00
Inventor 曹阳沈琴琴单小轩许云红朱森来
Owner NANTONG UNIVERSITY
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