Foundations of computational intelligence volume 2

approximate reasoning

Ajith Abraham, Francisco Herrera, Aboul-Ella Hassanien

<p>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.</p>


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3-25
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27-51
Fuzzy without fuzzy

Nguyen Hung T; Kreinovich Vladik; Modave François; Ceberio Martine

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53-74
Intermediate degrees are needed for the world to be cognizable

Nguyen Hung T; Kreinovich Vladik; Kosheleva Olga

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75-108
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111-131
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133-173
Computational methods for investment portfolio

Magoč Tanja; Modave François; Ceberio Martine; Kreinovich Vladik

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175-196
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197-236
Fuzzy logic control in communication networks

Chrysostomou Chrysostomos; Pitsillides Andreas

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237-258
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259-273
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275-293
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295-310

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