NDLI: Support vector regression based approach for key index forecasting with applications

Content Provider	IEEE Xplore Digital Library
Author	Shen Yin Fang Wu Hao Luo Huijun Gao
Copyright Year	2015
Description	Author affiliation: Sch. of Astronaut., Harbin Inst. of Technol., Harbin, China (Shen Yin; Fang Wu; Huijun Gao) \|\| Inst. of Autom. Control & Complex Syst., Univ. of Duisburg-Essen, Duisburg, Germany (Hao Luo)
Abstract	With the rapid development in science and technology, data acquisition, storage and mining technology are widely applied to various fields. All aspects of people's lives are recorded as data. Through the analyzing and arranging of data, people can get a lot of valuable information. In this paper, support vector machine (SVM), least squares support vector machine (LSSVM) and partial least squares (PLS) are respectively used in the field of economic research. Real-time monitoring and forecasting for stock index is vital to the market. The changing trend and index of stocks are predicted according to the analysis to the history data of the stock. By combining particle swarm algorithm (PSO) algorithm and LSSVM algorithm, the parameters in the LSSVM model can be optimized. These algorithms are compared on the basis of their forecasting results.
Starting Page	591
Ending Page	596
File Size	149979
Page Count	6
File Format	PDF
e-ISBN	9781479966493
DOI	10.1109/INDIN.2015.7281800
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-22
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Support vector machine regression Accuracy Particle swarm algorithm Least squares support vector machine Prediction algorithms Birds Data models Indexes Forecasting Real-time monitoring
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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