基于AIW-PSO小波神经网络的上证指数预测

摘要

In the view of the shortage of the Wavelet Neural Network Algorithm, adapt Adaptive Inertia Weight Particle Swarm Optimization Algorithm (AIW-PSO) as a study algorithm, build the AIW-PSO Wavelet Neural Network Model to predict the Shanghai stock Index., and make a comparison between the results of improved algorithm prediction model with results of traditional Wavelet Neural Network Model. The results show that the AIW-PSO Wavelet Neural Network Prediction Model has better prediction results on the Shanghai Stock Index.%针对小波神经网络(Wavelet Neural Network, WNN)的学习算法的不足，采用一种自适应惯性权重粒子群优化算法(Adaptive Inertia Weight Particle Swarm Optimization，AIW-PSO)作为小波神经网络的学习算法，建立AIW-PSO小波神经网络模型对上证指数进行预测，并将预测结果传统小波神经网络模型比较。结果表明，AIW-PSO小波神经网络模型对上证指数具有更好的预测效果。