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A hybrid swarm optimization for neural network training with application in stock price forecasting
Jianjia Pan1; Yuan Yan Tang1; Yulong Wang1; Xianwei Zheng1; Huiwu Luo1; Haoliang Yuan1; Patrick Shen Pei Wang2
2017-02-06
Conference Name2016 IEEE International Conference on Systems, Man, and Cybernetics • SMC 2016
Source Publication2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
Pages4450-4453
Conference Date9-12 Oct. 2016
Conference PlaceBudapest, Hungary
CountryHungary
PublisherIEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Abstract

A improved swarm optimization method based on particle swarm optimization (PSO) and simplified swarm optimization (SSO) is proposed to adjust the weight in artificial neural network. This method is a modification of traditional PSO and SSO, and combines them to a new optimization method (PSOSSO for short). The proposed method overcomes some of the drawbacks of SSO and improves its ability to train the weight of ANN. In the experiments, the PSOSSO is employed to train fuzzy wavelet neural network (FWNN) forecasting model to predict the prices of Hong Kong Hang Seng Index. The experimental results present that the PSOSSO is more efficient than traditional PSO and SSO methods.

DOIhttps://doi.org/10.1109/SMC.2016.7844932
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Cybernetics ; Computer Science, Information Systems
WOS IDWOS:000402634704044
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Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Department of Computer and Information Science Faculty of Science and Technology, University of Macau Macau SAR, China
2.College of Computer and Information Science Northeastern University, Boston, MA 02115, USA
First Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Jianjia Pan,Yuan Yan Tang,Yulong Wang,et al. A hybrid swarm optimization for neural network training with application in stock price forecasting[C]:IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA,2017:4450-4453.
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