Design And Implement Of City Area Parking Intelligent Management System Based On Bp Neural Network Forecast

With the economic development and improvement of people’s spending power, number of family cars is increasing fast,"parking problem" is getting worse. Existing standard parking areas cannot satisfy this demand and area parking can ease this situation. However, many problems such as disorder of area parking and imperfect of management system and arbitrary charges will result that administrative department cannot master information of parking and charge, so it is necessary to build a unified management system platform. In addition, majority of information forecast subsystem of domestic parking management system, can only display real-time parking space information, failed to predict changes in a short period of future, which will cause great difference between displaying information and real situation when the driver reaches the parking, even to look for another parking area, which is not very convenient.Firstly, this paper researches the development status of parking management system at home and abroad, points out the problems in the current work and analyses the reasons. And the paper discusses the relevant methods of time series forecasting methods, focused on the prediction based on neural network, and BP neural network prediction algorithm is in-depth research.Secondly, this paper analyses demand of this intelligent management system and completes the overall design work. First of all, in order to make the system intelligent, we divide it into four subsystems:parking information collection subsystem, handheld terminal charging subsystem, center management subsystem and parking guidance and information forecast subsystem. Communication format and interaction protocols are defined between various subsystems to achieve collection, transmission, processing and application of data. Then, parking information forecast function is introduced into the parking guidance subsystem, to achieve changing information of parking spaces in short-term of future. By comparing time series forecast methods, nonlinear time series forecasting and neural network forecasting, we ultimately create a parking information forecasting model based on BP neural network and use the actual data for verification.Finally, we complete the development and implementation of the system based on the actual needs of the project.