Due to the ability to handle specific characteristics of ecomics and finance forecasting problems like e.g. n-linear relationships, behavioral changes, or kwledge-based domain segmentation, we have recently witnessed a phemenal growth of the application of computational intelligence methodologies in this field. In this volume, Chen and Wang collected t just works on traditional computational intelligence approaches like fuzzy logic, neural networks, and genetic algorithms, but also examples for more recent techlogies 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 vel applications of these to typical ecomics and finance problems like business forecasting, currency crisis discrimination, foreign exchange markets, or stock markets behavior.
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
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Economics: Textbooks & Study Guides
Advanced Information Processing
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Springer-Verlag Berlin and Heidelberg GmbH & Co. K