Ebook: Hybrid Intelligent Systems: Analysis and Design

The objective of this edited volume is to offer a general view at the recent conceptual developments of Soft Computing (SC) regarded as a general methodology supporting the design of hybrid systems along with their diversified applications to modeling, simulation and control of non-linear dynamical systems. As of now, SC methodologies embrace neural networks, fuzzy logic, genetic algorithms and chaos theory. Each of these methodologies exhibits well delineated advantages and disadvantages. Interestingly, they have been found useful in solving a broad range of problems. However, many real-world complex problems require a prudent, carefully orchestrated integration of several of these methodologies to fully achieve the required efficiency, accuracy, and interpretability of the solutions. In this edited volume, an overview of SC methodologies, and their applications to modeling, simulation and control, will be given in an introductory paper by the Editors. Then, detailed methods for integrating the different SC methodologies in solving real-world problems will be given in the papers by the other authors in the book. The edited volume will cover a wide spectrum of applications including areas such as: robotic dynamic systems, non-linear plants, manufacturing systems, and time series prediction.

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The objective of this edited volume is to offer a general view at the recent conceptual developments of Soft Computing (SC) regarded as a general methodology supporting the design of hybrid systems along with their diversified applications to modeling, simulation and control of non-linear dynamical systems. As of now, SC methodologies embrace neural networks, fuzzy logic, genetic algorithms and chaos theory. Each of these methodologies exhibits well delineated advantages and disadvantages. Interestingly, they have been found useful in solving a broad range of problems. However, many real-world complex problems require a prudent, carefully orchestrated integration of several of these methodologies to fully achieve the required efficiency, accuracy, and interpretability of the solutions. In this edited volume, an overview of SC methodologies, and their applications to modeling, simulation and control, will be given in an introductory paper by the Editors. Then, detailed methods for integrating the different SC methodologies in solving real-world problems will be given in the papers by the other authors in the book. The edited volume will cover a wide spectrum of applications including areas such as: robotic dynamic systems, non-linear plants, manufacturing systems, and time series prediction.

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The objective of this edited volume is to offer a general view at the recent conceptual developments of Soft Computing (SC) regarded as a general methodology supporting the design of hybrid systems along with their diversified applications to modeling, simulation and control of non-linear dynamical systems. As of now, SC methodologies embrace neural networks, fuzzy logic, genetic algorithms and chaos theory. Each of these methodologies exhibits well delineated advantages and disadvantages. Interestingly, they have been found useful in solving a broad range of problems. However, many real-world complex problems require a prudent, carefully orchestrated integration of several of these methodologies to fully achieve the required efficiency, accuracy, and interpretability of the solutions. In this edited volume, an overview of SC methodologies, and their applications to modeling, simulation and control, will be given in an introductory paper by the Editors. Then, detailed methods for integrating the different SC methodologies in solving real-world problems will be given in the papers by the other authors in the book. The edited volume will cover a wide spectrum of applications including areas such as: robotic dynamic systems, non-linear plants, manufacturing systems, and time series prediction.
Content:
Front Matter....Pages I-XV
Front Matter....Pages I-XV
Hybridization Schemes in Architectures of Computational Intelligence....Pages 3-20
ChapBoltzmann Machines Learning Using High Order Decimation....Pages 21-42
Evolutionary Optimization of a Wiener Model....Pages 43-58
Synchronization of Chaotic Neural Networks: A Generalized Hamiltonian Systems Approach....Pages 59-73
Mediative Fuzzy Logic: A Novel Approach for Handling Contradictory Knowledge....Pages 75-91
Front Matter....Pages I-XV
Direct and Indirect Adaptive Neural Control of Nonlinear Systems....Pages 95-114
Simple Tuning of Fuzzy Controllers....Pages 115-133
From Type-1 to Type-2 Fuzzy Logic Control: A Stability and Robustness Study....Pages 135-149
A Comparative Study of Controllers Using Type-2 and Type-1 Fuzzy Logic....Pages 151-162
Evolutionary Computing for Topology Optimization of Type-2 Fuzzy Controllers....Pages 163-178
Front Matter....Pages I-XV
Decision Trees and CBR for the Navigation System of a CNN-based Autonomous Robot....Pages 181-201
Intelligent Agents in Distributed Fault Tolerant Systems....Pages 203-213
Genetic Path Planning with Fuzzy Logic Adaptation for Rovers Traversing Rough Terrain....Pages 215-228
Chattering Attenuation Using Linear-in-the-Parameter Neural Nets in Variable Structure Control of Robot Manipulators with Friction....Pages 229-241
Tracking Control for a Unicycle Mobile Robot Using a Fuzzy Logic Controller....Pages 243-253
Intelligent Control and Planning of Autonomous Algorithms Mobile Robots Using Fuzzy Logic and Genetic....Pages 255-265
Front Matter....Pages I-XV
The Role of Neural Networks in the Interpretation of Antique Handwritten Documents....Pages 269-281
Reasoning Object Recognition Using Fuzzy Inferential....Pages 283-297
The Fuzzy Sugeno Integral as a Decision Operator in the Recognition of Images with Modular Neural Networks....Pages 299-310
Modular Neural Networks and Fuzzy Sugeno Integral for Pattern Recognition: The Case of Human Face and Fingerprint....Pages 311-326
Front Matter....Pages I-XV
Optimal Training for Associative Memories: Application to Fault Diagnosis in Fossil Electric Power Plants....Pages 329-356
Acceleration Output Prediction of Buildings Using a Polynomial Artificial Neural Network....Pages 357-383
Time Series Forecasting of Tomato Prices and Processing in Parallel in Mexico Using Modular Neural Networks....Pages 385-402
Modular Neural Networks with Fuzzy Sugeno Integration Applied to Time Series Prediction....Pages 403-413
On Linguistic Summaries of Time Series Using a Fuzzy Quantifier Based Aggregation via the Sugeno Integral....Pages 415-433

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The objective of this edited volume is to offer a general view at the recent conceptual developments of Soft Computing (SC) regarded as a general methodology supporting the design of hybrid systems along with their diversified applications to modeling, simulation and control of non-linear dynamical systems. As of now, SC methodologies embrace neural networks, fuzzy logic, genetic algorithms and chaos theory. Each of these methodologies exhibits well delineated advantages and disadvantages. Interestingly, they have been found useful in solving a broad range of problems. However, many real-world complex problems require a prudent, carefully orchestrated integration of several of these methodologies to fully achieve the required efficiency, accuracy, and interpretability of the solutions. In this edited volume, an overview of SC methodologies, and their applications to modeling, simulation and control, will be given in an introductory paper by the Editors. Then, detailed methods for integrating the different SC methodologies in solving real-world problems will be given in the papers by the other authors in the book. The edited volume will cover a wide spectrum of applications including areas such as: robotic dynamic systems, non-linear plants, manufacturing systems, and time series prediction.
Content:
Front Matter....Pages I-XV
Front Matter....Pages I-XV
Hybridization Schemes in Architectures of Computational Intelligence....Pages 3-20
ChapBoltzmann Machines Learning Using High Order Decimation....Pages 21-42
Evolutionary Optimization of a Wiener Model....Pages 43-58
Synchronization of Chaotic Neural Networks: A Generalized Hamiltonian Systems Approach....Pages 59-73
Mediative Fuzzy Logic: A Novel Approach for Handling Contradictory Knowledge....Pages 75-91
Front Matter....Pages I-XV
Direct and Indirect Adaptive Neural Control of Nonlinear Systems....Pages 95-114
Simple Tuning of Fuzzy Controllers....Pages 115-133
From Type-1 to Type-2 Fuzzy Logic Control: A Stability and Robustness Study....Pages 135-149
A Comparative Study of Controllers Using Type-2 and Type-1 Fuzzy Logic....Pages 151-162
Evolutionary Computing for Topology Optimization of Type-2 Fuzzy Controllers....Pages 163-178
Front Matter....Pages I-XV
Decision Trees and CBR for the Navigation System of a CNN-based Autonomous Robot....Pages 181-201
Intelligent Agents in Distributed Fault Tolerant Systems....Pages 203-213
Genetic Path Planning with Fuzzy Logic Adaptation for Rovers Traversing Rough Terrain....Pages 215-228
Chattering Attenuation Using Linear-in-the-Parameter Neural Nets in Variable Structure Control of Robot Manipulators with Friction....Pages 229-241
Tracking Control for a Unicycle Mobile Robot Using a Fuzzy Logic Controller....Pages 243-253
Intelligent Control and Planning of Autonomous Algorithms Mobile Robots Using Fuzzy Logic and Genetic....Pages 255-265
Front Matter....Pages I-XV
The Role of Neural Networks in the Interpretation of Antique Handwritten Documents....Pages 269-281
Reasoning Object Recognition Using Fuzzy Inferential....Pages 283-297
The Fuzzy Sugeno Integral as a Decision Operator in the Recognition of Images with Modular Neural Networks....Pages 299-310
Modular Neural Networks and Fuzzy Sugeno Integral for Pattern Recognition: The Case of Human Face and Fingerprint....Pages 311-326
Front Matter....Pages I-XV
Optimal Training for Associative Memories: Application to Fault Diagnosis in Fossil Electric Power Plants....Pages 329-356
Acceleration Output Prediction of Buildings Using a Polynomial Artificial Neural Network....Pages 357-383
Time Series Forecasting of Tomato Prices and Processing in Parallel in Mexico Using Modular Neural Networks....Pages 385-402
Modular Neural Networks with Fuzzy Sugeno Integration Applied to Time Series Prediction....Pages 403-413
On Linguistic Summaries of Time Series Using a Fuzzy Quantifier Based Aggregation via the Sugeno Integral....Pages 415-433
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