Abstract：Back-Propagation Neural network is widely used by now,but the traditional back-propagation neural network has the disadvantages of slow convergence speed and easily fall into local optimum.In consideration of the automatically adjust search direction and good for global optimization by Genetic Algorithm,construction of Back-Propagation Neural Network Model Based on Genetic Algorithms,used on prediction the negative emotion of elderly people in the nursing house,key point of the feasibility in this model is the accuracy of prediction.In this paper,the data space of China Health and Retirement Longitudinal Study(CHARLS)based on Peking University Open Research Data Platform is taken as the main research data space.The prediction results show that both Partial Swarm Optimization(PSO)and Genetic Algorithm can improve the convergence speed of BP neural network,and avoid falling into local optimum.The PSO-BP neural network has faster convergence speed.The GA-BP neural network is better in accuracy.Considering that the nursing house do not have high requirements on the real-time data,the selection of Genetic Algorithm as the optimization scheme of BP neural network in negative emotion prediction is a better choice at the current stage.
王宇星,黄俊,潘英杰. GA-BP神经网络在老人负性情绪预测中的应用[J]. 小型微型计算机系统, 2020, 41(8): 1702-1706.
WANG Yu-xing,HUANG Jun,PAN Ying-jie. Application of Genetic Algorithm-back Propagation Neural Network in Negative Emotion Prediction for the Elderly. Journal of Chinese Computer Systems, 2020, 41(8): 1702-1706.
2020, Vol. 41 
