Road traffic flow parameter prediction method based on granular computing

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...

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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

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