Classification and Modeling with Linguistic Information Granules

Author:   Hisao Ishibuchi ,  Tomoharu Nakashima ,  Manabu Nii
Publisher:   Springer
ISBN:  

9783540800644


Pages:   320
Publication Date:   22 September 2008
Format:   Undefined
Availability:   Out of stock   Availability explained


Our Price $65.87 Quantity:  
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Classification and Modeling with Linguistic Information Granules


Overview

Whereas computer systems can easily handle even complicated and nonlinear mathematical models, human information processing is mainly based on linguistic knowledge. So the main advantage of using linguistic terms even with vague ranges is the intuitive interpretability of linguistic rules. Ishibuchi and his coauthors explain how classification and modeling can be handled in a human-understandable manner. They design a framework that can extract linguistic knowledge from numerical data by first identifying linguistic terms, then combining these terms into linguistic rules, and finally constructing a rule set from these linguistic rules. They combine their approach with state-of-the-art soft computing techniques such as multi-objective genetic algorithms, genetics-based machine learning, and fuzzified neural networks. Finally they demonstrate the usability of the combined techniques with various simulation results. In this largely self-contained volume, students specializing in soft computing will appreciate the detailed presentation, carefully discussed algorithms, and the many simulation experiments, while researchers will find a wealth of new design schemes, thorough analysis, and inspiring new research.

Full Product Details

Author:   Hisao Ishibuchi ,  Tomoharu Nakashima ,  Manabu Nii
Publisher:   Springer
Imprint:   Springer
Dimensions:   Width: 23.40cm , Height: 1.70cm , Length: 15.60cm
Weight:   0.449kg
ISBN:  

9783540800644


ISBN 10:   3540800646
Pages:   320
Publication Date:   22 September 2008
Audience:   General/trade ,  General
Format:   Undefined
Publisher's Status:   Unknown
Availability:   Out of stock   Availability explained

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