Advances in Computational Intelligence and Learning: Methods and Applications

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Hans-Jürgen Zimmermann, Georgios Tselentis, Maarten van Someren, Georgios Dounias
Springer Science & Business Media, Dec 6, 2012 - Mathematics - 515 pages

Advances in Computational Intelligence and Learning: Methods and Applications presents new developments and applications in the area of Computational Intelligence, which essentially describes methods and approaches that mimic biologically intelligent behavior in order to solve problems that have been difficult to solve by classical mathematics. Generally Fuzzy Technology, Artificial Neural Nets and Evolutionary Computing are considered to be such approaches.

The Editors have assembled new contributions in the areas of fuzzy sets, neural sets and machine learning, as well as combinations of them (so called hybrid methods) in the first part of the book. The second part of the book is dedicated to applications in the areas that are considered to be most relevant to Computational Intelligence.

 

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Contents

Should Tendency Assessment Precede Rule Extraction by Clustering? No
24
Adaptive Parameterization of Evolutionary Algorithms and Chaotic
117
NeuroFuzzy Systems for RuleBased Modelling
136
An Evaluation of Confidence Bound Estimation Methods for Neural
158
Unifying Learning with Evolution Through Baldwinian Evolution
160
Using An Evolutionary Strategy to Select Input Features for a Neural
173
Advances in Machine Learning 183
191
Fuzzy ModelBased Reinforcement Learning
212
About Robustness of Fuzzy Logic PD and PID Controller under Changes
315
Congestion Control for TCPIP DiffServ 343
342
Fuzzy Rule Based System for Diagnosis of Stone Construction Cracks
402
Automated Design of MultiDrilling Gear Machines
423
JAN JANTZEN HUBERTUS AXER AND DIEDRICH GRAF
465
Perspectives of Computational Intelligence
505
Index
512
Copyright

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