NDLI: The prediction of index in Shanghai stock based on genetic neural network

Content Provider	IEEE Xplore Digital Library
Author	Xijie Zang Jianli Yu
Copyright Year	2011
Description	Author affiliation: College of Science, Zhongyuan University of Technology, Zhengzhou, China (Xijie Zang) \|\| Zhengzhou Institute of Aeronautical Industry Management, China (Jianli Yu)
Abstract	In order to avoid shortcomings of the standard BP network algorithm, the forecast model in index of shanghai stock is constructed based on genetic neural network. Involving the advantages of GA and BP, the algorithm can simultaneously complete genetic selection within a solution space to find the optimal points. Then the BP algorithm searchs the best optimal result from those points by the direction of negative gradient. Thus it not only can avoid the BP algorithm into a local minimum and slow convergence etc, but also can overcome long-search time, slow shortcomings of the GA caused by searching optimal solution in a similar form of exhaustive. Simulation indicates that the algorithm is more accuracy than the standard BP algorithm, faster in calculation and very well in applicability.
Starting Page	5943
Ending Page	5946
File Size	172045
Page Count	4
File Format	PDF
ISBN	9781457705359
e-ISBN	9781457705366
DOI	10.1109/AIMSEC.2011.6011426
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-08
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genetic algorithm Artificial neural networks Time series Predictive models Genetics Prediction algorithms Search problems Neural network Indexes Stock maket Genetic algorithms
Content Type	Text
Resource Type	Article

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