Business Intelligence in Economic Forecasting: Technologies and Techniques: Technologies and Techniques

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· IGI Global
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With the rapid development of economic globalization and information technology, the field of economic forecasting continues its expeditious advancement, providing business and government with applicable technologies.

Business Intelligence in Economic Forecasting: Technologies and Techniques discusses various Business Intelligence techniques including neural networks, support vector machine, genetic programming, clustering analysis, TEI@I, fuzzy systems, text mining, and many more. This publication serves as a valuable reference for professionals and researchers interested in BI technologies and their practical applications in economic forecasting, as well as policy makers in business organizations and governments.

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Jue Wang received the PhD degree in Applied Mathematics from Xidian University, Xi?an in 2005. She is currently an assistant research fellow of Management Science at Academy of Mathematics and Systems Sciences of CAS. She has published 2 books and over 20 journal papers in journals including Soft Computing, Experts Systems with Applications. Her current research interests include financial engineering, data mining, intelligent computing, economic forecasting and decision analysis.

Shouyang Wang received the PhD degree in Operations Research from Institute of Systems Science, Chinese Academy of Sciences (CAS), Beijing in 1986. He is currently a Bairen distinguished professor of Management Science at Academy of Mathematics and Systems Sciences of CAS and a Lotus chair professor of Hunan University, Changsha. He is the editor-in-chief or a co-editor of 12 journals. He has published 18 books and over 180 journal papers. His current research interests include financial engineering, e-auctions, knowledge management and decision analysis. [Editor]

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