Application of BP neural network models and mind evolutionary algorithm in predicting stock composite indexes on Shanghai Stock Exchange

DOI

10.2991/iccsae-15.2016.39How to use a DOI?

Keywords

Mind evolutionary algorithm, Back propagation neural network, Shanghai Stock Exchange Composite Index, Stock Prediction.

Abstract

Stock composite indexes prediction is an important issue in the financial world. A back propagation neural network (BPNN) with mind evolutionary algorithm (MEA) developed for the prediction of prices on Shanghai Stock Exchange is presented. The optimum weights and threshold values of BPNN are determined by MEA, which solves partial minimization of BPNN. Experiments are performed with Shanghai Stock Exchange stock to determine the effectiveness of the model. The results indicate that the accuracy rate of the proposed model is more than 70%.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Guohao Lu
AU  - Changping Xie
AU  - Yingshu Zhang
AU  - Shaomei Fang
PY  - 2016/02
DA  - 2016/02
TI  - Application of BP neural network models and mind evolutionary algorithm in predicting stock composite indexes on Shanghai Stock Exchange
BT  - Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
PB  - Atlantis Press
SP  - 202
EP  - 205
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccsae-15.2016.39
DO  - 10.2991/iccsae-15.2016.39
ID  - Lu2016/02
ER  -