遗传算法优化BP神经网络的泊车位数量预测

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。

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

In order to improve the accuracy of short-term forecasting of spare parking spaces in parking lots, a prediction 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.