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This book comprises a selection of papers from IFSA 2007 on new methods for analysis and design of hybrid intelligent systems using soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including fuzzy logic, neural 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.
Expert systems (Computer science) --- Soft computing --- Hybrid computers --- Systèmes experts (Informatique) --- Informatique douce --- Calculateurs hybrides --- Congresses. --- Congrès --- Expert systems (Computer science) -- Congresses. --- Hybrid computers -- Congresses. --- Soft computing -- Congresses. --- Engineering & Applied Sciences --- Civil & Environmental Engineering --- Civil Engineering --- Applied Mathematics --- Computer Science --- Engineering. --- Artificial intelligence. --- Applied mathematics. --- Engineering mathematics. --- Appl.Mathematics/Computational Methods of Engineering. --- Artificial Intelligence (incl. Robotics). --- Applications of Mathematics. --- Engineering --- Engineering analysis --- Mathematical analysis --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Mathematics --- Mathematics. --- Mathematical and Computational Engineering. --- Artificial Intelligence. --- Math --- Science
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This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural networks with the aim of designing intelligent systems for complex pattern recognition problems, including iris, ear, face and voice recognition. The third part contains chapters with the theme of evolutionary optimization of type-2 fuzzy systems and modular neural networks in the area of intelligent pattern recognition, which includes the application of genetic algorithms for obtaining optimal type-2 fuzzy integration systems and ideal neural network architectures for solving problems in this area.
Pattern recognition systems --- Neural networks (Computer science) --- Fuzzy systems --- Engineering & Applied Sciences --- Electrical & Computer Engineering --- Electrical Engineering --- Computer Science --- Pattern recognition systems. --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Pattern classification systems --- Pattern recognition computers --- Engineering. --- Artificial intelligence. --- Pattern recognition. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Pattern Recognition. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Natural computation --- Pattern perception --- Computer vision --- Optical pattern recognition. --- Artificial Intelligence. --- Optical data processing --- Perceptrons --- Visual discrimination
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Mathematical statistics --- Artificial intelligence. Robotics. Simulation. Graphics --- patroonherkenning --- neuronale netwerken --- fuzzy logic --- cybernetica --- factoranalyse --- KI (kunstmatige intelligentie) --- robots
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This book describes recent advances on fuzzy logic augmentation of nature-inspired optimization metaheuristics and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. The book is organized in two main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of theoretical aspects of fuzzy logic augmentation of nature-inspired optimization metaheuristics, which basically consists of papers that propose new optimization algorithms enhanced using fuzzy systems. The second part contains papers with the main theme of application of optimization algorithms, which are basically papers using nature-inspired techniques to achieve optimization of complex optimization problems in diverse areas of application.
Engineering. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Artificial intelligence. --- Ingénierie --- Intelligence artificielle --- Engineering & Applied Sciences --- Computer Science --- Computational intelligence. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Artificial Intelligence. --- Fuzzy logic. --- Nonlinear logic --- Fuzzy mathematics --- Logic, Symbolic and mathematical --- Fuzzy systems
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This monograph describes new methods for intelligent pattern recognition using soft computing techniques including neural networks, fuzzy logic, and genetic algorithms. Hybrid intelligent systems that combine several soft computing techniques are needed due to the complexity of pattern recognition problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of pattern recognition systems, to achieve the ultimate goal of pattern recognition. This book also shows results of the application of hybrid intelligent systems to real-world problems of face, fingerprint, and voice recognition. This monograph is intended to be a major reference for scientists and engineers applying new computational and mathematical tools to intelligent pattern recognition and can be also used as a textbook for graduate courses in soft computing, intelligent pattern recognition, computer vision, or applied artificial intelligence.
Pattern recognition systems. --- Soft computing. --- Reconnaissance des formes (Informatique) --- Informatique douce --- Engineering. --- Artificial intelligence. --- Optical pattern recognition. --- Engineering mathematics. --- Appl.Mathematics/Computational Methods of Engineering. --- Pattern Recognition. --- Artificial Intelligence (incl. Robotics). --- Automation and Robotics. --- Signal, Image and Speech Processing. --- Neural networks (Computer science) --- Soft computing --- Pattern recognition systems --- Fuzzy systems --- Civil Engineering --- Computer Science --- Applied Mathematics --- Engineering & Applied Sciences --- Civil & Environmental Engineering --- Fuzzy systems. --- Neural networks (Computer science). --- Systems, Fuzzy --- Pattern classification systems --- Pattern recognition computers --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Engineering --- Engineering analysis --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Construction --- Mathematics --- Computer science. --- Computers. --- Pattern recognition. --- Applied mathematics. --- Control engineering. --- Robotics. --- Mechatronics. --- Computer Science. --- Theory of Computation. --- Control, Robotics, Mechatronics. --- Information theory. --- Mathematical and Computational Engineering. --- Artificial Intelligence. --- Mathematical analysis --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Communication theory --- Communication --- Cybernetics --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Signal processing. --- Image processing. --- Speech processing systems. --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Mechanical engineering --- Microelectronics --- Microelectromechanical systems --- Automation --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Programmable controllers --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Calculators --- Cyberspace
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This book describes new methods for building intelligent systems using type-2 fuzzy logic and soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including type-1 fuzzy logic, neural networks, and genetic algorithms, which can be used to create powerful hybrid intelligent systems. The authors extends the use of fuzzy logic to a higher order, which is called type-2 fuzzy logic. Combining type-2 fuzzy logic with traditional SC techniques, we can build powerful hybrid intelligent systems that can use the advantages that each technique offers. We consider in this book the use of type-2 fuzzy logic and traditional SC techniques to solve pattern recognition problems in realworld applications. This book is intended to be a major reference for scientists and engineers interested in applying type-2 fuzzy logic for solving problems in pattern recognition, intelligent control, intelligent manufacturing, robotics and automation. This book can also be used as a textbook or major reference for graduate courses like the following: soft computing, intelligent pattern recognition, computer vision, applied artificial intelligence, and similar ones.
Fuzzy logic --- Logique floue --- Civil Engineering --- Mathematical Theory --- Applied Mathematics --- Engineering & Applied Sciences --- Civil & Environmental Engineering --- Mathematics --- Physical Sciences & Mathematics --- Fuzzy logic. --- Logic, Symbolic and mathematical. --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Nonlinear logic --- Mathematics. --- Artificial intelligence. --- Mathematical logic. --- Applied mathematics. --- Engineering mathematics. --- Mathematical Logic and Foundations. --- Appl.Mathematics/Computational Methods of Engineering. --- Artificial Intelligence (incl. Robotics). --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Fuzzy mathematics --- Logic, Symbolic and mathematical --- Fuzzy systems --- Mathematical and Computational Engineering. --- Artificial Intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Engineering --- Engineering analysis --- Mathematical analysis
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Soft computing includes several intelligent computing paradigms, like fuzzy logic, neural networks, and bio-inspired optimization algorithms. This book describes the application of soft computing techniques to intelligent control, pattern recognition, and optimization problems. The book is organized in four main parts. The first part deals with nature-inspired optimization methods and their applications. Papers included in this part propose new models for achieving intelligent optimization in different application areas. The second part discusses hybrid intelligent systems for achieving control. Papers included in this part make use of nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for the optimal design of intelligent controllers for different kind of applications. Papers in the third part focus on intelligent techniques for pattern recognition and propose new methods to solve complex pattern recognition problems. The fourth part discusses new theoretical concepts and methods for the application of soft computing to many different areas, such as natural language processing, clustering and optimization.
Soft computing --- Intelligent control systems --- Pattern perception --- Mathematical optimization --- Engineering & Applied Sciences --- Computer Science --- Intelligent control systems. --- Mathematical optimization. --- Pattern perception. --- Soft computing. --- Design perception --- Pattern recognition --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Intelligent control --- Intelligent controllers --- Engineering. --- Artificial intelligence. --- Pattern recognition. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Pattern Recognition. --- Cognitive computing --- Electronic data processing --- Computational intelligence --- Form perception --- Perception --- Figure-ground perception --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Automatic control --- Optical pattern recognition. --- Artificial Intelligence. --- Optical data processing --- Perceptrons --- Visual discrimination --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Intelligence, Computational --- Artificial intelligence
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This book reviews current state of the art methods for building intelligent systems using type-2 fuzzy logic and bio-inspired optimization techniques. Combining type-2 fuzzy logic with optimization algorithms, powerful hy-brid intelligent systems have been built using the advantages that each technique offers. This book is intended to be a reference for scientists and engineers interested in applying type-2 fuzzy logic for solving problems in pattern recognition, intelligent control, intelligent manufacturing, robotics and automation. This book can also be used as a reference for graduate courses like the following: soft computing, intelligent pattern recognition, computer vision, applied artificial intelligence, and similar ones. We con-sider that this book can also be used to get novel ideas for new lines of re-search, or to continue the lines of research proposed by the authors.
Automatic control. --- Fuzzy logic. --- Fuzzy systems. --- Fuzzy logic --- Fuzzy systems --- Engineering & Applied Sciences --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Theory --- Computer Science --- Genetic algorithms. --- Fuzzy algorithms. --- Research. --- GAs (Algorithms) --- Genetic searches (Algorithms) --- Systems, Fuzzy --- Engineering. --- Artificial intelligence. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Algorithms --- Cluster set theory --- Fuzzy mathematics --- Combinatorial optimization --- Evolutionary computation --- Genetic programming (Computer science) --- Learning classifier systems --- System analysis --- Artificial Intelligence.
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In this book, a new method for hybrid intelligent systems is proposed. The proposed method is based on a granular computing approach applied in two levels. The techniques used and combined in the proposed method are modular neural networks (MNNs) with a Granular Computing (GrC) approach, thus resulting in a new concept of MNNs; modular granular neural networks (MGNNs). In addition fuzzy logic (FL) and hierarchical genetic algorithms (HGAs) are techniques used in this research work to improve results. These techniques are chosen because in other works have demonstrated to be a good option, and in the case of MNNs and HGAs, these techniques allow to improve the results obtained than with their conventional versions; respectively artificial neural networks and genetic algorithms.
Computer Science --- Engineering & Applied Sciences --- Neural networks (Computer science) --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Engineering. --- Artificial intelligence. --- Neural networks (Computer science). --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Mathematical Models of Cognitive Processes and Neural Networks. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Natural computation --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Artificial Intelligence. --- Neural networks (Computer science) .
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This book describes the latest advances in fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their applications in areas such as: intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and optimization of complex problems. The book is divided into five main parts. The first part proposes new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications; the second explores new concepts and algorithms in neural networks and fuzzy logic applied to recognition. The third part examines the theory and practice of meta-heuristics in various areas of application, while the fourth highlights diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical contexts. Finally, the fifth part focuses on applications of fuzzy logic, neural networks and meta-heuristics to robotics problems.
Fuzzy logic. --- Artificial intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Nonlinear logic --- Fuzzy mathematics --- Logic, Symbolic and mathematical --- Fuzzy systems --- Computational intelligence. --- Control engineering. --- Biomedical engineering. --- Computational Intelligence. --- Control and Systems Theory. --- Biomedical Engineering and Bioengineering. --- Clinical engineering --- Medical engineering --- Bioengineering --- Biophysics --- Engineering --- Medicine --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- Intelligence, Computational --- Artificial intelligence --- Soft computing
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