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Springer Soft Computing Applications in Business - Book 230

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Description

Explore the practical integration of advanced computational methods within the commercial sector. Soft Computing Applications in Business, part of the Studies in Fuzziness and Soft Computing series, provides a comprehensive collection of research papers focused on real-world business utility. This volume examines how soft computing techniques can be applied to solve complex problems in modern business environments. Readers will find detailed studies on diverse methodologies, including neural networks, data mining, and fuzzy decision trees. The text covers a broad spectrum of technical approaches such as Bayesian networks, ensemble learning, and case-based reasoning to help professionals and students understand the impact of these tools on decision-making and process optimization. By reviewing various applications like k-means clustering, hidden Markov models, and intelligent agents, this book serves as a valuable resource for understanding the mathematical and algorithmic foundations used in today's data-driven business landscape.

Key Features

Comprehensive collection of research papers covering essential soft computing techniques used across various business sectors.

Detailed technical coverage of methodologies including neural networks, Bayesian networks, and data mining for business applications.

In-depth exploration of clustering and learning methods such as k-means clustering, biclustering, and ensemble learning.

Covers advanced decision-making tools like fuzzy decision trees, Dempster-Shafer theory, and case-based reasoning.

Includes studies on probabilistic and evolutionary approaches such as hidden Markov models and evolutionary programming.

Provides insights into intelligent systems through topics like intelligent agents and opportunistic scheduling.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
29 April 2008
Listed Since
12 March 2008

Barcode

No barcode data available

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