Coordination Model of Rail Transit Operation Scheduling Based on Fuzzy Control Algorithm Development and Verification

Abstract

Under the trend of developing all-round three-dimensional transportation network in our country, urban rail transit system has become an important means to solve urban congestion with its superior performance. By regulating the distribution of human re-sources and rationalizing the use of material resources, rail transit system can bring maximum economic benefits to operators and maximize benefits for society, which is a hot topic of social discus-sion and attention at present. Based on fuzzy control algorithm, congestion entropy is used to improve the multi-group hierarchical joint optimization algorithm. Then, FNN (Fuzzy Neural Network), an intelligent method, is applied to the study of the interval time of urban rail transit, and a FNN model is constructed with reference to the mathematical model. Finally, the trained network is tested to verify the feasibility of FNN in determining the driving interval of urban rail transit.