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Springer Recent Developments in Ordered Weighted Averaging Operators - Theory and Practice

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Description

This comprehensive volume explores the latest advances and practical applications of OWA (ordered weighted averaging) operators, originally developed by Ronald R. Yager in the early 1980s. The book presents a state-of-the-art overview of new theoretical developments and real-world implementations of these powerful aggregation operators. OWA operators offer conceptual simplicity combined with numerical strength, making them easily implementable across diverse problem domains. This Springer publication, part of the Studies in Fuzziness and Soft Computing series (Volume 265), addresses both foundational research and extensions of OWA operators, whilst exploring their applications across computing, artificial intelligence, machine learning, and related fields. Ideal for researchers, academics, and practitioners seeking to understand and apply advanced aggregation techniques in complex decision-making scenarios.

Key Features

Springer Studies in Fuzziness and Soft Computing series volume 265 covers foundational theory and modern extensions of ordered weighted averaging operators.

Explores practical applications of OWA operators across computing, artificial intelligence, and machine learning domains.

Presents Ronald R. Yager's original ordered weighted averaging concept with contemporary developments and implementations.

Combines theoretical foundations with real-world case studies demonstrating the versatility and power of aggregation operators.

Addresses both advanced research and accessible explanations for academics and practitioners in computer science and AI fields.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
03 February 2011
Listed Since
22 November 2010

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