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Springer Soft Computing for Knowledge Discovery - Book 570

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Description

Explore the fundamentals of pattern recognition and data analysis with Soft Computing for Knowledge Discovery. This book provides a systematic exposition of the theory and algorithms required to uncover useful patterns in data, allowing computers to perform tasks autonomously or assist humans more efficiently. Written as part of the Springer International Series in Engineering and Computer Science, this text offers a self-contained look at knowledge discovery through a soft computing lens. It covers essential topics including knowledge representation and machine learning. Readers will find detailed information on the core methodologies of the field, such as fuzzy set theory, fuzzy logic, and evolutionary computing. This resource is designed for those studying the fabric of soft computing and its application to modern data challenges.

Key Features

Provides a systematic exposition of key theory and algorithms used in the core of knowledge discovery.

Covers essential soft computing methodologies including fuzzy set theory, fuzzy logic, and evolutionary computing.

Focuses on practical applications of knowledge representation and machine learning for data analysis.

Designed to help computers perform tasks autonomously by identifying interesting patterns in data.

Part of the Springer International Series in Engineering and Computer Science for academic depth.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
31 August 2000
Listed Since
15 December 2006

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