基于GA-Elman动态回归神经网络的股价预测模型研究

文章针对股价预测问题的复杂性、不确定性、时变性及动态性等特性,利用Elman神经网络具有记忆性的优点,采用遗传算法训练优化Elman神经网络的初始权值,提出了高效的GA-Elman动态回归神经网络股价预测模型。实验模拟结果表明:该模型快速稳定且具有较高的精度,将其用于股票价格预测可行且有效。该模型的提出也为股票价格预测提供了一种新的技术和方法。

Stock Market Forecasting Research Based on GA-Elman Neural Network

Based on characteristics of stock prices and the merits of Elman networks,this paper establishes a GA-Elman neural network model, in which Genetic Algorithm is used to optimize the weight values.So the model efficiently solves the problems of complexity,uncertainty and dynamic characteristics of stock prices prediction.Simulation results show that the proposed GAElman neural network is feasible and efficient.This paper provides a new method for modeling and forecasting in stock market.