Advances in Computational Intelligence and Learning: Methods and Applications

Overview

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 ...

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Overview

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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Product Details

  • ISBN-13: 9789401038720
  • Publisher: Springer Netherlands
  • Publication date: 4/30/2013
  • Series: International Series in Intelligent Technologies , #18
  • Edition description: Softcover reprint of the original 1st ed. 2002
  • Edition number: 1
  • Pages: 515
  • Product dimensions: 6.14 (w) x 9.21 (h) x 1.08 (d)

Table of Contents

Preface
Accuracy and Transparency of Fuzzy Systems 3
Should Tendency Assessment Precede Rule Extraction by Clustering? (No!) 17
A Review of Wavelet Networks, Wavenets, Fuzzy Wavenets and their Applications 43
Investigating Neural Network Efficiency and Structure by Weight Investigation 61
An Evaluation of Confidence Bound Estimation Methods for Neural Networks 71
Compensation of Periodic Disturbances in Continuous Processing Plants by Means of a Neural Controller 85
Predictive Control with Restricted Genetic Optimisation 107
Adaptive Parameterization of Evolutionary Algorithms and Chaotic Populations 117
Neuro-Fuzzy Systems for Rule-Based Modelling of Dynamic Processes 135
Hybrid Intelligent Architectures using a Neurofuzzy Approach 147
Unifying Learning with Evolution Through Baldwinian Evolution and Lamarckism 159
Using An Evolutionary Strategy to Select Input Features for a Neural Network Classifier 169
Advances in Machine Learning 183
Symbolic and Neural Learning of Named-Entity Recognition and Classification Systems in Two Languages 193
Fuzzy Model-Based Reinforcement Learning 211
A Cellular Space for Feature Extraction and Classification 225
A Fuzzy Approach to Taming the Bullwhip Effect 247
Forecast of Short Term Trends in Stock Exchange using Fuzzy Rules and Neural Networks on Multiresolution Processed Signals 263
Customer Relationship Management: A Combined Approach by Customer Segmentation and Database Marketing 281
A new Vendor Evaluation Product for SAP R/3 Systems 291
About Robustness of Fuzzy Logic PD and PID Controller under Changes of Reasoning Methods 307
Control of MIMO Dead Time Processes Using Fuzzy Relational Models 319
Fuzzy Sliding Mode Controllers Synthesis through Genetic Optimization 331
Fuzzy RED: Congestion Control for TCP/IP Diff-Serv 343
The Use of Reinforcement Learning Algorithms in Traffic Control of High Speed Networks 353
Fuzzy Reasoning in WCDMA Radio Resource Functions 371
Odour Classification based on Computational Intelligence Techniques 383
Fuzzy Rule Based System for Diagnosis of Stone Construction Cracks of Buildings 401
Automated Design of Multi-Drilling Gear Machines 413
Optimal Design of Alloy Steels Using Genetic Algorithms 425
Intelligent Systems in Biomedicine 437
Diagnosis Of Aphasia Using Neural And Fuzzy Techniques 461
Gene Expression Data Mining for Functional Genomics using Fuzzy Technology 475
Symbolic, Neural and Neuro-fuzzy Approaches to Pattern Recognition in Cardiotocograms 489
Perspectives of Computational Intelligence 501
Index 514
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