Computational Intelligence in Economics and Finance (Advanced Information Processing)
Editorial Reviews
Book Description
Due to the ability to handle specific characteristics of economics and finance forecasting problems like e.g. non-linear relationships, behavioral changes, or knowledge-based domain segmentation, we have recently witnessed a phenomenal growth of the application of computational intelligence methodologies in this field. In this volume, Chen and Wang collected not just works on traditional computational intelligence approaches like fuzzy logic, neural networks, and genetic algorithms, but also examples for more recent technologies like e.g. rough sets, support vector machines, wavelets, or ant algorithms. After an introductory chapter with a structural description of all the methodologies, the subsequent parts describe novel applications of these to typical economics and finance problems like business forecasting, currency crisis discrimination, foreign exchange markets, or stock markets behavior.
Book Info
Text discusses traditional computational intelligence approaches like fuzzy logic, neural networks, and genetic algorithms. Also examines examples involving more recent technologies such as rough sets, support vector machines, wavelets, and ant algorithms.
Computational Intelligence in Economics and Finance (Advanced Information Processing),Shu-Heng Chen,Paul P. Wang,Springer,3540440984,Accounting - General,Artificial Intelligence - General,Business & Economics,Business/Economics,Computers - General Information,Data processing,Economics,Economics - General,Economics, Mathematical,Finance,Management Information Systems,Ants Algorithm,Artificial Intelligence,Business Forecasting,Computers / Artificial Intelligence,Economic Modelling,Economic forecasting,Financial Data Mining,Financial Engineering,Genetic Programming,Neural Networks Applications,Pattern Matching,Rough Sets Theory,Self-Organizing Maps,State Space Modeling,Support Vector Machines,Time Series Modeling,Wavelets
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