基于NB-IoT技术和GA-BP神经网络的车位预测系统  

Parking Space Prediction Based on NB-IoT Technology and GA-BP Neural Network

作　　者：李伟[1] 梁睿君[1] 宋丹 LI Wei;LIANG Ruijun;SONG Dan(College of Mechanical and Electronic Engineering,Nanjing University of Aeronautics&Astronautics,Nanjing,210016,China)

机构地区：[1]南京航空航天大学机电学院,南京210016

出　　处：《南京航空航天大学学报》2020年第3期454-459,共6页Journal of Nanjing University of Aeronautics & Astronautics

基　　金：国家自然科学基金(51575272)资助项目。

摘　　要：围绕有效整合城市停车资源,提高现有车位存量利用率的需求,构建了一种基于NB-IoT技术的车位预测系统。该系统采用NB-IoT技术进行信息采集与传输实现车位信息的共享;考虑到车位状态信息实时变化的特性,用历史车位占用数据来建立车位预测模型,推测出未来短时内车位变化趋势。为了提高车位预测的精度,采用遗传算法(Genetic algorithm,GA)优化反向传播(Back propagtion,BP)神经网络建立GA-BP神经网络车位预测模型。以某地下停车场历史数据为例进行仿真实验,研究结果表明:车位预测模型预测值与实际值相近且趋势保持一致,能够有效准确的预测车位状态变化,具有较高的精度。The paper aims to effectively integrating city parking resources and increasing the utilization of existing parking spaces.An intelligent parking prediction system based on NB-IoT technology is constructed.The system uses NB-IoT technology for information collection and transmission to realize the sharing of parking space information;The real-time changes of the parking space status information is considered,and the historical parking space occupancy data is used to establish the parking space prediction model,so as to infer the future short-term parking space change trend.Genetic algarithm(GA)-back propagation(BP)neural network parking space prediction model is established to improve the accuracy of parking space prediction.We take the historical data of an underground parking lot as an example,and the simulation results show that the predicted value of the prediction model is similar to the actual value and their trends are consistent,which can effectively and accurately predict the change of parking space state and has high precision.

关 键 词：智能停车系统 NB-IoT技术 遗传算法-反向传播神经网络 车位预测 

分 类 号：TH165[机械工程—机械制造及自动化]