Researches on Intelligent Parking Method of Parking Lot Based on Forecast and Multi-attribute Decision-making

摘要

For solving supply and demand balance between the parking space of parking lots and the car of the drivers, on the basis of analyzing time series forecasting techniques, the forecasting method using BP neural network algorithm was presented to forecast the parking lots free parking spaces, which was effective through MATLAB simulation. By analysis the drivers' main consideration about how to choose a parking space, the decision attribute matrix was identified by driving distance which was deduced through Dijkstra algorithm, walking distance was deduced through Euclidean distance and parking space environment value that was deduced through the entropy of triangular fuzzy number. Finally, using the grey correlation entropy method of MADM to sorting the effective free parking spaces, the optimal attributes of free parking spaces was the optimal free parking spaces.