Computational Intelligence in Economics and Finance: Volume II, 2. sējumsPaul P. Wang, Tzu-Wen Kuo Springer Science & Business Media, 2007. gada 11. jūl. - 228 lappuses Computational intelligence (CI), as an alternative to statistical and econometric approaches, has been applied to a wide range of economics and finance problems in recent years, for example to price forecasting and market efficiency. This book contains research ranging from applications in financial markets and business administration to various economics problems. Not only are empirical studies utilizing various CI algorithms presented, but so also are theoretical models based on computational methods. In addition to direct applications of computational intelligence, readers can also observe how these methods are combined with conventional analytical methods such as statistical and econometric models to yield preferred results. Chen, Wang, and Kuo have grouped the 12 contributions following their introductory chapter into applications of fuzzy logic, neural networks (including self-organizing maps and support vector machines), and evolutionary computation. All chapters were selected either by invitation or based on a careful selection and extension of best papers from the International Workshop on Computational Intelligence in Economics and Finance in 2005. Overall, the book offers researchers an excellent overview of current advances and applications of computational intelligence techniques to economics and finance problems. |
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1.–5. rezultāts no 56.
... Production: LE-TEX Jelonek, Schmidt & Vöckler GbR, Leipzig Cover design: KünkelLopka Werbeagentur, Heidelberg Printed on acid-free paper 45/3180/YL - 5 4 3 2 1 0 Preface It was mostly during the last twenty five years Editors.
... papers from a larger group presented during their organizedInternational Workshop on Computational Intelligence in Economics and Finance of 2005 (CIEF2005) held as part of the 8th Joint Conference on Information Sciences (JCIS2005) V ...
... papers to include in this volume also successfully managed to choose a large number of research efforts that utilizes computational intelligence techniques when investigating market efficiency and predicting financial market conditions ...
... papers were encouraged to submit their extended versions of the conference papers to the post conference publications. Twenty-seven submissions were received, and each of them was sent to at least two referees. In the end, only nine out ...
... paper can be particularly helpful for researchers who want to tackle similar problems of their own. 4.3 Support Vector Machines The support vector machine (SVM) was introduced in the previous volume ([18], pp.18–20). Two chapters there ...
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1 | |
An Overview of Insurance Uses of Fuzzy Logic | 24 |
ArnoldF Shapiro 25 | 63 |
Estimating Female Labor Force Participation through Statistical | 93 |
An Application of Kohonens SOFM to the Management | 106 |
Trading Strategies Based on Kmeans Clustering and Regression Models | 123 |
Application of an Instance Based Learning Algorithm for Predicting | 144 |
Nonlinear GoalDirected CPPI Strategy | 183 |
A LogicalHeuristic Approach | 209 |
Index | 224 |
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Computational Intelligence in Economics and Finance: Volume II Paul P. Wang,Tzu-Wen Kuo Priekšskatījums nav pieejams - 2010 |
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