The Application Of Fuzzy Bayesian Decision In The Urban Traffic System

In recent years, urban traffic congestion has been deteriorating, and optimizing andchoosing the transport routes can help save time and reduce costs. Therefore, it issignificant to do relevant researches. The research object for this paper is the smooth flowof urban traffic system. In order to select the most appropriate routes, the study estimatesthe traffic conditions using Bayesian statistics on the basis of fuzzy mathematics andstatistics. The main works for the thesis are as follows:(1) Review some basic concepts and principles of fuzzy theory;(2) Based on the analysis of Bayesian decision-making process, apply fuzzy theory toevery stage of decision-making, from which one can obtain the continuous fuzzy Bayesiandecision-making method, as well as greatly expand the ranges of the Bayesiandecision-making application;(3) In combination with the actual situations of urban traffic, put the decision-makingmethod mentioned in part (2) into practice, and achieve ideal results.There are three types of information in Bayesian theory, namely, priori information,sample information and a posteriori information. Based on these types the study proposesthe continuous fuzzy Bayesian decision-making method:①deal with the priori information and the sample information in according to thefuzzy theory;②based on the conventional Bayesian probability formula, transform thepriori information and the sample information into posteriori information using thedefinition of the intersection from the fuzzy theory;③utilize the fuzzy posterioriprobability obtained above and the loss function to make decisions.Through the analysis mentioned above, the research studies the feasibility of theapplication of the continuous fuzzy Bayesian decision-making method, and applies it tothe transport network. From which the purpose of optimizing and choosing the transportroutes is achieved.