£155.99

Springer Computational Intelligence in Economics and Finance

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Description

Explore the rapid growth of computational intelligence methodologies within the fields of economics and finance. This volume by Chen and Wang addresses the unique challenges of forecasting, such as non-linear relationships, behavioral changes, and knowledge-based domain segmentation. As traditional models face new complexities, this book provides a comprehensive look at how advanced information processing can be applied to financial data. It covers a wide spectrum of methodologies, ranging from established techniques to modern technological advancements. Readers will find detailed explorations of how these tools help manage the specific characteristics inherent in economic forecasting problems. This text serves as a valuable resource for understanding the application of intelligent systems in modern financial environments. It bridges the gap between theoretical computational intelligence and practical economic application, offering a deep dive into the technologies shaping the future of the industry.

Key Features

Covers traditional computational intelligence approaches including fuzzy logic, neural networks, and genetic algorithms.

Includes recent technological developments such as rough sets, support vector machines, wavelets, and ant colony optimization.

Addresses specific forecasting challenges like non-linear relationships and behavioral changes in economic data.

Provides insights into knowledge-based domain segmentation for more accurate financial modeling.

Explores the application of advanced information processing methodologies to modern economics and finance problems.

Product Specifications

Format
Hardcover
Domain
Amazon UK
Release Date
16 September 2003
Listed Since
23 December 2006

Barcode

No barcode data available

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