Road traffic flow parameter prediction method based on granular computing

A forecasting method and traffic flow technology, applied in the direction of traffic flow detection, etc., can solve the problems of lack of adaptability and low reliability.

Active Publication Date: 2015-12-23
丁宏飞 +7
View PDF6 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Aiming at the technical problems of low reliability of road traffic flow parameter prediction and lack of adaptable dynamic prediction in the prior art, the present invention discloses a road traffic flow parameter prediction method based on granular computing

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Road traffic flow parameter prediction method based on granular computing
  • Road traffic flow parameter prediction method based on granular computing
  • Road traffic flow parameter prediction method based on granular computing

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0023] The specific implementation manners of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0024] The invention discloses a road traffic flow parameter prediction method based on granular computing, which specifically includes the following steps: step 1, according to the detected value range span of the traffic flow parameter, define the research scope and determine the number of information particles; step 2. Define the fuzzy set within the research scope, and determine the subordinate relationship between the detected traffic flow parameter data and the fuzzy set; wherein the number of fuzzy sets is the same as the number of information particles; Step 3, determine the logical relationship between the fuzzy sets, Obtain the fuzzy relationship group; step 4, use the fuzzy time series to estimate the interval of information particles, so as to predict the traffic flow parameters in the next time period. The present i...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The present invention relates to the field of traffic information release and traffic management and control and discloses a road traffic flow parameter prediction method based on granular computing. The method comprises the steps of (1) replacing a data point by information particulate to be the basic unit of data mining analysis, (2) with granular computing ideology throughout the whole prediction framework, taking granular processing as a data processing method with a unified structure, allowing a policy maker to clearly understand the positions of various forms of systems in mutual interaction, grasping the communication mode of the systems, and establishing an enhanced harmonious environment among different ways, (3) with a fuzzy time series and the Gath-Geva cluster theory as the basis, by focusing on the commonalities of existing formal methods, recognizing the orthogonality of an existing good frame ( such as the probability theory and the probability density functions of various variables), with variable granularity concept as a basis, establishing the interval length analysis model of a granularity range according to a numerical entity, and thus realizing pattern recognition and speculation on the above basis.

Description

technical field [0001] The invention relates to the fields of traffic information release and traffic management and control, in particular to a method for predicting road traffic flow parameters based on granular computing. Background technique [0002] Traffic flow parameter prediction is an important basis for traffic flow guidance and traffic information release. In the context of urban traffic, the traffic flow is based on the dynamic changes in the time domain, so the prediction of traffic flow parameters is a problem based on the dynamic processing of the time domain. Traditional forecasting methods are difficult to find a balance point in precision and dynamic processing, causing the forecast results to deviate from the actual traffic parameter data change trend. [0003] Song and Chissom (1993) first proposed the concept of fuzzy time series. Compared with traditional fuzzy sets, it has good changing characteristics in the dynamic time domain. In recent years, fuz...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01
Inventor 丁宏飞罗霞刘博刘硕智秦政李演洪宋阳高续
Owner 丁宏飞
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap