Analysis and Design of Intelligent Systems Using Soft Computing Techniques

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Patricia Melin, Oscar Castillo, Eduardo G. Ramírez, Witold Pedrycz
Springer Science & Business Media, Sep 20, 2007 - Mathematics - 855 pages
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This book comprises a selection of papers from IFSA 2007 on new methods for ana- sis and design of hybrid intelligent systems using soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including fuzzy logic, n- ral networks, and genetic algorithms, which can be used to produce powerful hybrid intelligent systems for solving problems in pattern recognition, time series prediction, intelligent control, robotics and automation. Hybrid intelligent systems that combine several SC techniques are needed due to the complexity and high dimensionality of real-world problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of these systems, for this reason it is very important to optimize architecture design. The architectures can combine, in different ways, neural networks, fuzzy logic and genetic algorithms, to achieve the ultimate goal of pattern recognition, time series prediction, intelligent control, or other application areas. This book is intended to be a major reference for scientists and engineers interested in applying new computational and mathematical tools to design hybrid intelligent systems. This book can also be used as a reference for graduate courses like the f- lowing: soft computing, intelligent pattern recognition, computer vision, applied ar- ficial intelligence, and similar ones. The book is divided in to twelve main parts. Each part contains a set of papers on a common subject, so that the reader can find similar papers grouped together.
 

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Contents

Performance Improvement of the Attitude Estimation System Using Fuzzy Inference and Genetic Algorithms
445
Multi Objective Optimization in Machining Operations
455
Evolutionary Computing for the Optimization of Mathematical Functions
463
Providing Intelligence to Evolutionary Computational Methods
473
Part VII Fuzzy Modeling
482
Representing Fuzzy Numbers for Fuzzy Calculus
483
Fuzzy Parallel Processing of Hydro Power Plants Why Not?
495
A Dynamic Method of Experiment Design of Computer Aided Sensory Evaluation
504

Theory and Applications
76
A Case Study
79
MFCM for Nonlinear Blind Channel Equalization
88
Fuzzy Rules Extraction from Support Vector Machines for Multiclass Classification
99
Density Based Fuzzy Support Vector Machines for Multicategory Pattern Classification
109
A Modified FCM Algorithm for Fast Segmentation of Brain MR Images
119
Incorporation of Noneuclidean Distance Metrics into Fuzzy Clustering on Graphics Processing Units
128
A Comparative Study
140
Improved Fuzzy CMeans Segmentation Algorithm for Images with Intensity Inhomogeneity
150
Part III Intelligent Identification and Control
160
A FuzzyNeural Hierarchical Multimodel for Systems Identification and Direct Adaptive Control
163
Robust Speed Controller Design Method Based on Fuzzy Control for Torsional Vibration Suppression in TwoMass System
173
Selforganizing Fuzzy Controller Based on Fuzzy Neural Network
185
Decision Making Strategies for RealTime Train Dispatch and Control
195
Soft Margin Training for Associative Memories Implemented by Recurrent Neural Networks
205
Part IV Time Series Prediction
215
Modular Neural Networks with Fuzzy Integration Applied for Time Series Forecasting
216
Predicting Job Completion Time in a Wafer Fab with a Recurrent Hybrid Neural Network
226
A Hybrid ANNFIR System for Lot Output Time Prediction and Achievability Evaluation in a Wafer Fab
236
MFactor High Order Fuzzy Time Series Forecasting for Road Accident Data
246
A Realistic Method to Forecast Gross Domestic Capital of India
255
Design of Modular Neural Networks with Fuzzy Integration Applied to Time Series Prediction
265
Part V Pattern Recognition
274
Characterize the Parameters of Genetic Algorithms Based on Zernike Polynomials for Recovery of the Phase of Interferograms of Closed Fringes Usi...
275
Rotated Coin Recognition Using Neural Networks
290
Selected Problems of Intelligent Handwriting Recognition
298
3D Object Recognition Using an Ultrasonic Sensor Array and Neural Networks
306
Soft System for Road Sign Detection
316
Nonlinear Neurofuzzy Network for Channel Equalization
327
On the Possibility of Reliably Constructing a Decision Support System for the Cytodiagnosis of Breast Cancer
337
Spatial Heart Simulation and Analysis Using Unified Neural Network
346
A Method for Creating Ensemble Neural Networks Using a Sampling Data Approach
355
Pattern Recognition Using Modular Neural Networks and Fuzzy Integral as Method for Response Integration
365
Part VI Evolutionary Computation
374
A Differential Evolution Algorithm for Fuzzy Extension of Functions
375
Use of ParetoOptimal and Near ParetoOptimal Candidate Rules in Genetic Fuzzy Rule Selection
387
A Dissimilation Particle Swarm OptimizationBased Elman Network and Applications for Identifying and Controlling Ultrasonic Motors
397
A Cultural Algorithm for Solving the Set Covering Problem
408
Integration of Production and Distribution Planning Using a Genetic Algorithm in Supply Chain Management
416
Bacteria Swarm Foraging Optimization for Dynamical Resource Allocation in a Multizone Temperature Experimentation Platform
427
An Ant Colony Optimization plugin to Enhance the Interpretability of Fuzzy Rule Bases with Exceptions
436
Measure of Uncertainty in Regional Grade Variability
511
PCTOPSIS Method for the Selection of a Cleaning System for Engine Maintenance
519
Coordination Uncertainty of Belief Measures in Information Fusion
530
TwoInput Fuzzy TPE Systems
539
Intelligent Decision Support System
549
An Adaptive Location Service on the Basis of Fuzzy Logic for MANETs
558
Part VIII Intelligent Manufacturing and Scheduling
566
Fuzzy Logic Based Replica Management Infrastructure for Balanced Resource Allocation and Efficient Overload Control of the Complex ServiceOrie...
567
A FuzzyNeural Approach with BPN Postclassification for Job Completion Time Prediction in a Semiconductor Fabrication Plant
580
Enhanced Genetic AlgorithmBased Fuzzy Multiobjective Strategy to Multiproduct Batch Plant Design
590
A Novel Approach for Reasoning in Possibilistic Logic
600
Applying GeneticFuzzy Approach to Model Polyester Dyeing
608
Gear Fault Diagnosis in Time Domains by Using Bayesian Networks
618
An Intelligent Hybrid Algorithm for JobShop Scheduling Based on Particle Swarm Optimization and Artificial Immune System
628
Fuzzy Multicriteria Decision Making Method for Machine Selection
638
Fuzzy Goal Programming and an Application of Production Process
649
The Usage of Fuzzy Quality Control Charts to Evaluate Product Quality and an Application
660
Part IX Intelligent Agents
674
An Intelligent BeliefDesireIntention Agent for Digital GameBased Learning
675
Improved Scheme for Telematics Fault Tolerance with Agents
686
Multiagent Based Integration of Production and Distribution Planning Using Genetic Algorithm in the Supply Chain Management
696
Modeling and Simulation by Petri Networks of a Fault Tolerant Agent Node
707
Part X Neural Networks Theory
717
The Game of Life Using Polynomial Discrete Time Cellular Neural Networks
719
Wavelet Networks Approach
727
Support Vector MachineBased ECG Compression
737
Tuning FCMP to Elicit Novel Time Course Signatures in fMRI Neural Activation Studies
746
Part XI Robotics
756
Moving Object Tracking Using the Particle Filter and SOM in Robotic Space with Network Sensors
757
Robust Stability Analysis of a Fuzzy Vehicle Lateral Control System Using Describing Function Method
769
A Comparative Study for a Drone
780
Optimal Path Planning for Autonomous Mobile Robot Navigation Using Ant Colony Optimization and a Fuzzy Cost Function Evaluation
790
Intelligent Control and Planning of Autonomous Mobile Robots Using Fuzzy Logic and Multiple Objective Genetic Algorithms
799
Part XII Fuzzy Logic Applications
808
Generalized Reinforcement Learning Fuzzy Control with Vague States
809
New Cluster Validity Index with Fuzzy Functions
821
A Fuzzy Model for Supplier Selection and Development
831
A Neurofuzzy Multiobjective Design of Shewhart Control Charts
842
Author Index
853
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Page 31 - ... gives a crisp number at the output of the fuzzy system, the extended defuzzification operation in the type-2 case gives a type-1 fuzzy set at the output. Since this operation takes us from the type-2 output sets of the fuzzy system to a type-1 set, we can call this operation "type reduction" and call the type-1 fuzzy set so obtained a "type-reduced set".

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