人工智能算法在股票价格波动规律预测中的应用

Application of Artificial Intelligence Algorithm in Predicting Regularity of Stock Price Fluctuation

针对当前股票交易价格模型动荡性、高冗余及高噪音等问题,建立了基于人工智能算法的新的预测模型,利用RBM结构深度神经网络学习算法提取原始特征向量及内在信息,实践证实该预测模型具有较高的计算精度,且能够促进预测模型学习非线性关系能力的提升,可实现对股票价格波动规律的精准预测,在股票涨跌投资判断中具有一定的参考价值。

In view of the problems of volatility,high redundancy and high noise in the current stock trading price model,a new prediction model based on artificial intelligence algorithm is established,in which the original feature vector and intrinsic information are extracted by using deep neural network learning algorithm of RBM structure.It is turned out that the prediction model has high calculation precision,and can promote the improvement of ability of learning nonlinear relationship and realize accurate prediction of stock price fluctuation regularity,having a certain reference value in the judgment of investing the stock.