Study On Location Of Shared Bicycle Parking Points In Universities Based On Grey Relational Model

In a shared bicycle swept the major city in the process,there are many parked,lying and other uncivilized parking behavior,even in the civilization of the relatively high quality of the campus is no exception.In order to achieve the goal of detailed design and order management in the sharing of bicycle system in Colleges,we need to take all factors into consideration and set up evaluation index system and comparison method,so as to select the best plan for the implementation of parking management layout plan in Colleges and universities.Through the induction and study of the location factors of bicycle parking spots at home and abroad,this paper preliminarily selects several evaluation indexes of parking space selection by means of questionnaire survey,and uses the method of fuzzy clustering analysis to classify and optimize the primary selection index,avoiding the shadow of correlation between the indexes.Ringing.Through the optimization,this paper classifies the location selection index from 3 levels of use,implementation and management,establishes an evaluation system containing 6 evaluation indexes,and gives the specific definition and quantitative method of each index.On this basis,put forward the grey relation analysis of shared bicycle stops location plan selection based on the analysis of the effectiveness of the use of normalization of the evaluation indicators,determine the index weight by entropy method,and then according to the grey relation principle of alternatives for each study within the scope of the sort select the best solution.The method is applied to the Department of Chang'an University Institute of North Campus bicycle stops sharing location research,to select the best bike stop school sharing layout plan,and will select the best bike sharing stops and the status quo of docking point analysis and comparing the advantages and disadvantages of the research.The results show that this method can provide more effective decision support for sharing the location of single parking lots in universities,and also make up for the blank of research on location planning of shared parking places in high speed lines.