Soft Computing New Trends and Applications

In the last decade new artificial intelligence methods for the modelling and control of complex systems, namely neural networks, fuzzy logic and probabilistic reasoning have drawn the interest of researchers and engineers. Recently, the advantages achievable by using combinations of these methods, w...

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Bibliographic Details
Main Authors: Fortuna, Luigi, Rizzotto, Gianguido (Author), Lavorgna, Mario (Author), Nunnari, Giuseppe (Author)
Format: eBook
Language:English
Published: London Springer London 2001, 2001
Edition:1st ed. 2001
Series:Advanced Textbooks in Control and Signal Processing
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
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245 0 0 |a Soft Computing  |h Elektronische Ressource  |b New Trends and Applications  |c by Luigi Fortuna, Gianguido Rizzotto, Mario Lavorgna, Giuseppe Nunnari, Maria Gabriella Xibilia, Riccardo Caponetto 
250 |a 1st ed. 2001 
260 |a London  |b Springer London  |c 2001, 2001 
300 |a XII, 267 p. 58 illus  |b online resource 
505 0 |a 1. Introduction -- 2. Fuzzy Logic -- 3. Fuzzy Control -- 4. Artificial Neural Networks -- 5. Neural Networks for Modeling and Controlling Dynamical Systems -- 6. Evolutionary Optimization Algorithm -- 7. Cellular Neural Networks -- 8. Complex Dynamics and Cellular Neural Networks -- 9. Neuro-fuzzy Networks -- 10. Fuzzy Cellular Neural Networks -- 11. Fuzzy Systems Optimization by Means of Genetic Algorithms -- 12. Neuro-fuzzy Strategies for Monitoring Urban Traffic Noise -- 13. Modeling and Control of a Robot for Picking Citrus Fruit -- 14. Modeling and Control of RTP Systems -- 15. A Neural Network to Predict Air Pollution in Industrial Areas -- 16. Conclusions 
653 |a Control, Robotics, Automation 
653 |a Computer-Aided Engineering (CAD, CAE) and Design 
653 |a Applied Dynamical Systems 
653 |a Artificial Intelligence 
653 |a Computer-aided engineering 
653 |a Nonlinear theories 
653 |a Control engineering 
653 |a Artificial intelligence 
653 |a Robotics 
653 |a Automation 
653 |a Dynamics 
700 1 |a Rizzotto, Gianguido  |e [author] 
700 1 |a Lavorgna, Mario  |e [author] 
700 1 |a Nunnari, Giuseppe  |e [author] 
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490 0 |a Advanced Textbooks in Control and Signal Processing 
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520 |a In the last decade new artificial intelligence methods for the modelling and control of complex systems, namely neural networks, fuzzy logic and probabilistic reasoning have drawn the interest of researchers and engineers. Recently, the advantages achievable by using combinations of these methods, which have independent origin and evolution, have been pointed out, generating a new paradigm which is now termed "soft-computing". This new methodology subsumes the capabilities of neural networks for modelling non-linear systems and for solving classification problems, the power of fuzzy-logic to represent approximate or heuristic reasoning and the large capabilities of evolutionary computation for problem optimisation. The book presents a clear understanding of a new type of computation system, the cellular neural network (CNN), which has been successfully applied to the solution of many heavy computation problems, mainly in the fields of image processing and complex partial differential equations. CNNs' computation-based systems represent new opportunities for improving the soft-computation toolbox. The application of soft computing to complex systems and in particular to chaotic systems with the generation of chaotic dynamics by using CNN is also described. These aspects are of particular interest owing to their growing interest for research and application purposes. Specific topics covered in the text include: - fuzzy logic, control and neural networks; - artificial neural networks and their application in the modelling and control of dynamical systems; - evolutionary optimisation algorithms; - complex dynamics and cellular neural networks; - applications in urban traffic noise monitoring, robot control and rapid thermal process systems