Title :
BP Neural Network Model Based on the K-Means Clustering to Predict the Share Price
Author :
Zhang, Jichao ; Yang, Yueting
Author_Institution :
Sch. of Math., Inst. of Appl. Math., Jilin, China
Abstract :
A preprocessing procedure on dense type of data is presented using the error back propagation algorithm. In this paper, K-means are applied to BP neural network such that the data is preprocessed for the neural network. So appropriate pretreatment techniques of data could make the neural network execute more effectively to accept intensive data. Furthermore, some comparisons between the proposed algorithm and other algorithms will be provided. The BP algorithm may be applied to solve more practical nonlinear problem.
Keywords :
backpropagation; economic forecasting; neural nets; pattern clustering; share prices; stock markets; BP algorithm; BP neural network model; K-means clustering; data dense type; data preprocessing; data pretreatment technique; error backpropagation algorithm; intensive data; nonlinear problem; share price prediction; stock price forecasting; Clustering algorithms; Indexes; Mathematical model; Neural networks; Predictive models; Stock markets; Time series analysis; BP neural network; K-means; data preprocessing; stock price forecasting; time series;
Conference_Titel :
Computational Sciences and Optimization (CSO), 2012 Fifth International Joint Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4673-1365-0
DOI :
10.1109/CSO.2012.46
