Knowledge Processing with Interval and Soft Computing

Massive datasets, made available today by modern technologies, present a significant challenge to scientists who need to effectively and efficiently extract relevant knowledge and information. Due to their ability to model uncertainty, interval and soft computing techniques have been found to be eff...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Hu, Chenyi (Editor ), Baker Kearfott, R. (Editor ), de Korvin, Andre (Editor ), Kreinovich, Vladik (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Springer London : Imprint: Springer, 2008.
Edición:1st ed. 2008.
Colección:Advanced Information and Knowledge Processing,
Temas:
Data mining.
Application software.
Mathematics.
Computer science-Mathematics.
Discrete mathematics.
Artificial intelligence.
Data Mining and Knowledge Discovery.
Computer and Information Systems Applications.
Applications of Mathematics.
Discrete Mathematics in Computer Science.
Artificial Intelligence.
Acceso en línea:Texto Completo
Descripción
Sumario:Massive datasets, made available today by modern technologies, present a significant challenge to scientists who need to effectively and efficiently extract relevant knowledge and information. Due to their ability to model uncertainty, interval and soft computing techniques have been found to be effective in this extraction. This book provides coverage of the basic theoretical foundations for applying these techniques to artificial intelligence and knowledge processing. The first three chapters provide the background needed for those who are unfamiliar with interval and soft computing techniques. The following chapters describe innovative algorithms and their applications to knowledge processing. In particular, these chapters cover computing techniques for interval linear systems of equations, interval matrix singular-value decomposition, interval function approximation, and decision making with statistical and graph-based data processing. To enable these applications, the book presents a standards-based object-oriented interval computing environment in C++. By providing the necessary background and summarizing recent results and successful applications, this self-contained book will serve as a useful resource for researchers and practitioners wanting to learn interval and soft computing techniques and apply them to artificial intelligence and knowledge processing.
Descripción Física:XII, 233 p. 61 illus. online resource.
ISBN:9781848003262
ISSN:2197-8441

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