Foundations of Computational Intelligence Aboul-Ella Hassanien, Ajith Abraham and Francisco Herrera editors Volume 2 Approximate reasoning /

Contributor(s):

Material type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9783642015328

Other title:

Approximate reasoning

Subject(s):

DDC classification:

23 006.31 HAS

Online resources:

Table of Contents only

Summary: Annotation Human reasoning usually is very approximate and involves various types of uncertainties. Approximate reasoning is the computational modelling of any part of the process used by humans to reason about natural phenomena or to solve real world problems. The scope of this book includes fuzzy sets, Dempster-Shafer theory, multi-valued logic, probability, random sets, and rough set, near set and hybrid intelligent systems. Besides research articles and expository papers on theory and algorithms of approximation reasoning, papers on numerical experiments and real world applications were also encouraged. This Volume comprises of 12 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Intelligence techniques for approximation reasoning. The Volume is divided into 2 parts: Part-I: Approximate Reasoning Theoretical Foundations and Part-II: Approximate Reasoning Success Stories and Real World Applications.

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Holdings
Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	Gifted Books	Sai University Library General stacks				006.31 HAS (Browse shelf(Opens below))					Available			G2977

Gifted by Ajith Abraham

Includes bibliographical references and index

Annotation Human reasoning usually is very approximate and involves various types of uncertainties. Approximate reasoning is the computational modelling of any part of the process used by humans to reason about natural phenomena or to solve real world problems. The scope of this book includes fuzzy sets, Dempster-Shafer theory, multi-valued logic, probability, random sets, and rough set, near set and hybrid intelligent systems. Besides research articles and expository papers on theory and algorithms of approximation reasoning, papers on numerical experiments and real world applications were also encouraged. This Volume comprises of 12 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Intelligence techniques for approximation reasoning. The Volume is divided into 2 parts: Part-I: Approximate Reasoning Theoretical Foundations and Part-II: Approximate Reasoning Success Stories and Real World Applications.

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