Study On The Forecast Of Urban Rail Transit Passenger Flow Based On Grey Theory

With the rapid development of economy and the continuous expansion of urban population,serious traffic congestion has occurred,and automobile exhaust and noise pollution have been aggravated.The construction of urban rail transit plays a key role in alleviating road traffic and reducing pollution.Safety,speediness,comfort,convenience,economy,environmental protection and other advantages makes Urban rail transit plays an important role in public transport and becomes the best way for people to travel.The prediction of passenger flow is an important basis for the planning,design,construction and operation of urban rail transit.At the same time,the accuracy of passenger flow prediction also has a great impact on the work of each stage of urban rail transit.In this paper,the fuzzy grey prediction method is used to predict the passenger flow of urban rail transit.Taking Lanzhou Rail Transit Line 1 as an example,the prediction results of the fuzzy grey prediction model are analyzed and verified.Firstly,the classification,influencing factors and characteristics of passenger flow of urban rail transit are studied,and the variation rules of urban rail transit passenger flow in time and space are analyzed in detail,the characteristics of passenger flow of urban rail transit are summarized.At the same time,according to the passenger flow data of Lanzhou Rail Transit Line 1 after operation,this paper analyzes and summarizes the passenger flow characteristics of Lanzhou Rail Transit Line 1.Secondly,it summarizes the relevant contents of urban rail transit passenger flow prediction,including forecast index,forecast years and forecast mode.This paper analyzes and studies several common methods of passenger flow forecast in urban rail transit.Through the comparison and analysis of these methods,it determines the prediction method researched and applied in this paper,namely grey prediction method.Thirdly,in order to overcome the problem that all historical data of grey prediction method have the same weight,the fuzzy set theory is introduced to construct the urban rail transit passenger flow prediction method of the fuzzy grey prediction model.In this model,the original data of grey prediction are fuzzified by fuzzy membership function,and the fuzzy weakening buffer sequence is obtained by using weighted average weakening buffer operator.This series fully reflects the grey system’s "emphasis on near but light on far",which can effectively improve the forecasting accuracy.Finally,the fuzzy grey prediction model is verified by the passenger flow data of Lanzhou Rail Transit Line 1.Through the analysis of the prediction results,it is found that the prediction accuracy of the prediction model is good,and it has a good effect on the prediction of urban rail transit passenger flow.The research and application of fuzzy grey prediction model provides data support for the operation and management of Lanzhou Rail Transit Line 1,and also provides corresponding reference for the passenger flow prediction and operation management of other urban rail transit.