Overview
- Editors:
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Aboul-Ella Hassanien
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Faculty of Computers and Information Information Technology Department, Cairo University, Orman, Giza
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Ajith Abraham
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Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, Auburn,Washington, USA
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Francisco Herrera
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Soft Computing and Intelligent Information Systems Department of Computer Science and Artificial Intelligence ETS de Ingenierias Informática y de Telecomunicación, University of Granada, Granada, Spain
- Second volume of a Reference work on the foundations of Computational Intelligence
- Devoted to approximate reasoning
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About this book
Foundations of Computational Intelligence Volume 2: Approximation Reasoning: Theoretical Foundations and Applications Human reasoning usually is very approximate and involves various types of - certainties. 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 t- ory 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 - proximation reasoning. The Volume is divided into 2 parts: Part-I: Approximate Reasoning – Theoretical Foundations Part-II: Approximate Reasoning – Success Stories and Real World Applications Part I on Approximate Reasoning – Theoretical Foundations contains four ch- ters that describe several approaches of fuzzy and Para consistent annotated logic approximation reasoning. In Chapter 1, “Fuzzy Sets, Near Sets, and Rough Sets for Your Computational Intelligence Toolbox” by Peters considers how a user might utilize fuzzy sets, near sets, and rough sets, taken separately or taken together in hybridizations as part of a computational intelligence toolbox. In multi-criteria decision making, it is necessary to aggregate (combine) utility values corresponding to several criteria (parameters).
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Table of contents (12 chapters)
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Approximate Reasoning - Theoretical Foundations and Applications
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Approximate Reasoning - Theoretical Foundations
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- Hung T. Nguyen, Vladik Kreinovich, François Modave, Martine Ceberio
Pages 27-51
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- Hung T. Nguyen, Vladik Kreinovich, J. Esteban Gamez, François Modave, Olga Kosheleva
Pages 53-74
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Approximate Reasoning - Success Stories and Real World Applications
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Front Matter
Pages 109-109
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- Tanja Magoč, François Modave, Martine Ceberio, Vladik Kreinovich
Pages 133-173
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- Chrysostomos Chrysostomou, Andreas Pitsillides
Pages 197-236
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- Wenxin Jiang, Alicja Wieczorkowska, Zbigniew W. Raś
Pages 259-273
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- El-Sayed A. El-Dahshan, Aboul Ella Hassanien, Amr Radi, Soumya Banerjee
Pages 275-293
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- Huiyu Zhou, Gerald Schaefer
Pages 295-310
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Editors and Affiliations
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Faculty of Computers and Information Information Technology Department, Cairo University, Orman, Giza
Aboul-Ella Hassanien
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Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, Auburn,Washington, USA
Ajith Abraham
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Soft Computing and Intelligent Information Systems Department of Computer Science and Artificial Intelligence ETS de Ingenierias Informática y de Telecomunicación, University of Granada, Granada, Spain
Francisco Herrera