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Computational Intelligence Systems and Applications: Neuro-Fuzzy and Fuzzy Neural Synergisms - Couverture rigide
Synopsis
Traditional Artificial Intelligence (AI) systems adopted symbolic processing as their main paradigm. Symbolic AI systems have proved effective in handling problems characterized by exact and complete knowledge representation. Unfortunately, these systems have very little power in dealing with imprecise, uncertain and incomplete data and information which significantly contribute to the description of many real- world problems, both physical systems and processes as well as mechanisms of decision making. Moreover, there are many situations where the expert domain knowledge (the basis for many symbolic AI systems) is not sufficient for the design of intelligent systems, due to incompleteness of the existing knowledge, problems caused by different biases of human experts, difficulties in forming rules, etc. In general, problem knowledge for solving a given problem can consist of an explicit knowledge (e.g., heuristic rules provided by a domain an implicit, hidden knowledge "buried" in past-experience expert) and numerical data. A study of huge amounts of these data (collected in databases) and the synthesizing of the knowledge "encoded" in them (also referred to as knowledge discovery in data or data mining), can significantly improve the performance of the intelligent systems designed.
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Computational Intelligence Systems and Applications: Neuro-Fuzzy and Fuzzy Neural Synergisms (Studies in Fuzziness and Soft Computing, 86)
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Physica, 2001
ISBN 10 : 3790814393
ISBN 13 : 9783790814392
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Couverture rigide
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Etat : Acceptable. Used - Acceptable. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library with wear and barcode page may have been removed. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. N° de réf. du vendeur Z1-B-033-02114
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Computational Intelligence Systems and Applications: Neuro-Fuzzy and Fuzzy Neural Synergisms (Studies in Fuzziness and Soft Computing, 86)
Edité par
Physica, 2001
ISBN 10 : 3790814393
ISBN 13 : 9783790814392
Ancien ou d'occasion
Couverture rigide
Vendeur : Phatpocket Limited, Waltham Abbey, HERTS, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : Like New. Used - Like New. Book is new and unread but may have minor shelf wear. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. N° de réf. du vendeur Z1-T-039-00502
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Computational Intelligence Systems and Applications : Neuro-Fuzzy and Fuzzy Neural Synergisms
Edité par
Physica-Verlag HD, 2001
ISBN 10 : 3790814393
ISBN 13 : 9783790814392
Ancien ou d'occasion
Couverture rigide
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Etat : Sehr gut. Zustand: Sehr gut | Seiten: 380 | Sprache: Englisch | Produktart: Bücher. N° de réf. du vendeur 338412/2
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Computational Intelligence Systems and Applications
Edité par
Physica-Verlag HD, 2001
ISBN 10 : 3790814393
ISBN 13 : 9783790814392
Neuf
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Self-contained presentation of new concepts and structures of CI systems and their real-life applicationsTraditional Artificial Intelligence (AI) systems adopted symbolic processing as their main paradigm. Symbolic AI systems have proved effective in ha. N° de réf. du vendeur 5310389
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Computational Intelligence Systems and Applications
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Springer, Berlin, Physica-Verlag HD, Physica Dez 2001, 2001
ISBN 10 : 3790814393
ISBN 13 : 9783790814392
Neuf
Couverture rigide
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Traditional Artificial Intelligence (AI) systems adopted symbolic processing as their main paradigm. Symbolic AI systems have proved effective in handling problems characterized by exact and complete knowledge representation. Unfortunately, these systems have very little power in dealing with imprecise, uncertain and incomplete data and information which significantly contribute to the description of many real world problems, both physical systems and processes as well as mechanisms of decision making. Moreover, there are many situations where the expert domain knowledge (the basis for many symbolic AI systems) is not sufficient for the design of intelligent systems, due to incompleteness of the existing knowledge, problems caused by different biases of human experts, difficulties in forming rules, etc. In general, problem knowledge for solving a given problem can consist of an explicit knowledge (e.g., heuristic rules provided by a domain an implicit, hidden knowledge 'buried' in past-experience expert) and numerical data. A study of huge amounts of these data (collected in databases) and the synthesizing of the knowledge 'encoded' in them (also referred to as knowledge discovery in data or data mining), can significantly improve the performance of the intelligent systems designed. 364 pp. Englisch. N° de réf. du vendeur 9783790814392
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Computational Intelligence Systems and Applications : Neuro-Fuzzy and Fuzzy Neural Synergisms
Edité par
Physica-Verlag HD, 2001
ISBN 10 : 3790814393
ISBN 13 : 9783790814392
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Traditional Artificial Intelligence (AI) systems adopted symbolic processing as their main paradigm. Symbolic AI systems have proved effective in handling problems characterized by exact and complete knowledge representation. Unfortunately, these systems have very little power in dealing with imprecise, uncertain and incomplete data and information which significantly contribute to the description of many real world problems, both physical systems and processes as well as mechanisms of decision making. Moreover, there are many situations where the expert domain knowledge (the basis for many symbolic AI systems) is not sufficient for the design of intelligent systems, due to incompleteness of the existing knowledge, problems caused by different biases of human experts, difficulties in forming rules, etc. In general, problem knowledge for solving a given problem can consist of an explicit knowledge (e.g., heuristic rules provided by a domain an implicit, hidden knowledge 'buried' in past-experience expert) and numerical data. A study of huge amounts of these data (collected in databases) and the synthesizing of the knowledge 'encoded' in them (also referred to as knowledge discovery in data or data mining), can significantly improve the performance of the intelligent systems designed. N° de réf. du vendeur 9783790814392
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Computational Intelligence Systems and Applications: Neuro-Fuzzy and Fuzzy Neural Synergisms (Studies in Fuzziness and Soft Computing, 86)
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Computational Intelligence Systems and Applications
Edité par
Physica-Verlag HD Dez 2001, 2001
ISBN 10 : 3790814393
ISBN 13 : 9783790814392
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Traditional Artificial Intelligence (AI) systems adopted symbolic processing as their main paradigm. Symbolic AI systems have proved effective in handling problems characterized by exact and complete knowledge representation. Unfortunately, these systems have very little power in dealing with imprecise, uncertain and incomplete data and information which significantly contribute to the description of many real world problems, both physical systems and processes as well as mechanisms of decision making. Moreover, there are many situations where the expert domain knowledge (the basis for many symbolic AI systems) is not sufficient for the design of intelligent systems, due to incompleteness of the existing knowledge, problems caused by different biases of human experts, difficulties in forming rules, etc. In general, problem knowledge for solving a given problem can consist of an explicit knowledge (e.g., heuristic rules provided by a domain an implicit, hidden knowledge 'buried' in past-experience expert) and numerical data. A study of huge amounts of these data (collected in databases) and the synthesizing of the knowledge 'encoded' in them (also referred to as knowledge discovery in data or data mining), can significantly improve the performance of the intelligent systems designed.Physica Verlag, Tiergartenstr. 17, 69121 Heidelberg 380 pp. Englisch. N° de réf. du vendeur 9783790814392
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Computational Intelligence Systems and Applications: Neuro-Fuzzy and Fuzzy Neural Synergisms (Studies in Fuzziness and Soft Computing, 86)
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Computational Intelligence Systems and Applications: Neuro-Fuzzy and Fuzzy Neural Synergisms (Studies in Fuzziness and Soft Computing, 86)
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