Abstract
In order to study the prediction problem of expressway travel time, due to the ambiguity and uncertainty in the road traffic system, the travel time prediction model is established based on the exclusive disjunctive soft set theory. Through the parameter reduction theory of soft set, the main influence factors are extracted, and the mapping relationship between the influence factors and the travel time is obtained through the exclusive disjunctive soft set decision system. The travel time model is established based on the soft set theory, and the travel time is calculated through the mapping relationship. The experimental results show that, compared with the BPR function model, the travel time model based on the exclusive disjunctive soft set theory reduces the prediction error and effectively improves the calculation accuracy of the travel time.
Highlights
With the rapid development of intelligent transportation system, the traffic information that can be obtained and provided is more and more abundant, and the travel time prediction is an indispensable part of the advanced highway travel information system.Facing the increasingly prominent traffic problems, dynamic traffic control and traveller behavior decision-making require highway travel time prediction
From the point of view of data mining, this paper introduces the exclusive disjunctive soft set to describe the incomplete information system, and quantifies the data in the incomplete information system by redefining the characteristic functions in the exclusive disjunctive soft set
Soft set theory as a new mathematical method to solve the problem of uncertainty obtains fast development, the paper introduces the exclusive disjunctive soft set, and proposes to systemize the incomplete information into the exclusive disjunctive soft set decision system, so that the exclusive disjunctive soft set can process the decision analysis based on the incomplete information system
Summary
With the rapid development of intelligent transportation system, the traffic information that can be obtained and provided is more and more abundant, and the travel time prediction is an indispensable part of the advanced highway travel information system.Facing the increasingly prominent traffic problems, dynamic traffic control and traveller behavior decision-making require highway travel time prediction. It is important to improve the accuracy of the estimation when considering the estimated value, it is of great practical significance to quantitatively describe the uncertainty of the predicted value. When studying the travel time, the following problems are rarely considered: the judgment of the traffic participants on the traffic state is inherently vague, not precise. The ambiguity should be fully considered for the estimation and prediction of the travel time. Soft sets are powerful theories for dealing with ambiguity and uncertainty, its advantages are for quantitative analysis, and for qualitative analysis [10,11,12].
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