遗传算法优化BP神经网络的泊车位数量预测  

Prediction of spare parking spaces based on BP neural network optimized by genetic algorithm

作　　者：张金梦 刘慧君[1] ZHANG Jinmeng, LIU Huijun(College of Computer Science, Chongqing University, Chongqing 400044, P.R.Chin)

机构地区：[1]重庆大学计算机学院,重庆400044

出　　处：《重庆大学学报（自然科学版）》2018年第3期76-81,共6页Journal of Chongqing University

基　　金：国家自然科学基金资助项目(61272194)~~

摘　　要：为了提高停车场空余泊车位短时预测的精度,利用遗传算法优化BP(back propagation)神经网络的权值和阈值,建立了基于GABP(genetic algorithm back propagation)神经网络的有效泊车位数量的预测模型,并对该预测模型进行训练,最终得到最优解。实验结果表明,该方法对泊车位数量预测具有更高的预测精度,且非线性拟合能力显著。In order to improve the accuracy of short-term forecasting of spare parking spaces in parking lots,aprediction method based on back propagation（BP）neural network optimized by genetic algorithm（GA）is presented.The GA is used to optimize the weights and thresholds of BP neural network,and the BP neural network is trained to search for the optimal solution.The simulation results show that the proposed method has better prediction accuracy,and the nonlinear fitting ability is significant.

关 键 词：有效泊车位 遗传算法 BP神经网络 预测 

分 类 号：TP305[自动化与计算机技术—计算机系统结构]