Publicado por Physica, 2002
Idioma: Inglés
Librería: Antiquariat Thomas Haker GmbH & Co. KG, Berlin, Alemania
Miembro de asociación: GIAQ
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Añadir al carritoHardcover. Condición: Wie neu. 282 S.; Ill. Like new. Shrink wrapped. Sprache: Englisch Gewicht in Gramm: 705.
Librería: Phatpocket Limited, Waltham Abbey, HERTS, Reino Unido
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Añadir al carritoCondición: 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.
Publicado por Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Heidelberg, 2011
ISBN 10: 3790825204 ISBN 13: 9783790825206
Idioma: Inglés
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 106,86
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Añadir al carritoPaperback. Condición: new. Paperback. This book presents a variety of recently developed methods for generating fuzzy rules from data with the help of neural networks and evolutionary algorithms. Special efforts have been put on dealing with knowledge incorporation into neural and evolutionary systems and knowledge extraction from data with the help of fuzzy logic. On the one hand, knowledge that is understandable to human beings can be extracted from data using evolutionary and learning methods by maintaining the interpretability of the generated fuzzy rules. On the other hand, a priori knowledge like expert knowledge and human preferences can be incorporated into evolution and learning, taking advantage of the knowledge representation capability of fuzzy rule systems and fuzzy preference models. Several engineering application examples in the fields of intelligent vehicle systems, process modeling and control and robotics are presented. Compared to heuristic fuzzy rules, fuzzy rules generated from data are able to extract more profound knowledge for more complex systems. This book presents a number of approaches to the generation of fuzzy rules from data, ranging from the direct fuzzy inference based to neural net works and evolutionary algorithms based fuzzy rule generation. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Publicado por Berlin Springer Verlag, 2002
ISBN 10: 3790815373 ISBN 13: 9783790815375
Idioma: Inglés
Librería: CSG Onlinebuch GMBH, Darmstadt, Alemania
EUR 43,52
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Añadir al carritoGebunden. Condición: Sehr gut. Gebraucht - Sehr gut Zustand: Sehr gut, X, 271 p. 180 illus. About this book This book presents a variety of recently developed methods for generating fuzzy rules from data with the help of neural networks and evolutionary algorithms. Special efforts have been put on dealing with knowledge incorporation into neural and evolutionary systems and knowledge extraction from data with the help of fuzzy logic. On the one hand, knowledge that is understandable to human beings can be extracted from data using evolutionary and learning methods by maintaining the interpretability of the generated fuzzy rules. On the other hand, a priori knowledge like expert knowledge and human preferences can be incorporated into evolution and learning, taking advantage of the knowledge representation capability of fuzzy rule systems and fuzzy preference models. Several engineering application examples in the fields of intelligent vehicle systems, process modeling and control and robotics are presented. Written fo scientists.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 140,12
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Añadir al carritoCondición: New. pp. 284.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 127,62
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
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Añadir al carritoCondición: New. Using neural networks and evolutionary algorithms, this book presents a variety of recently developed methods for generating fuzzy rules from data. It considers knowledge incorporation into neural and evolutionary systems and knowledge extraction from data with fuzzy logic. Series: Studies in Fuzziness and Soft Computing. Num Pages: 272 pages, 228 black & white illustrations, 10 black & white tables, biography. BIC Classification: PBWX; UMB; UYQ. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 233 x 155 x 17. Weight in Grams: 586. . 2003. 2003rd Edition. Hardcover. . . . .
Librería: Revaluation Books, Exeter, Reino Unido
EUR 152,17
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Añadir al carritoPaperback. Condición: Brand New. 282 pages. 9.25x6.00x0.75 inches. In Stock.
Publicado por Physica-Verlag HD Nov 2002, 2002
ISBN 10: 3790815373 ISBN 13: 9783790815375
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 106,99
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Añadir al carritoBuch. Condición: Neu. Neuware -Fuzzy rule systems have found a wide range of applications in many fields of science and technology. Traditionally, fuzzy rules are generated from human expert knowledge or human heuristics for relatively simple systems. In the last few years, data-driven fuzzy rule generation has been very active. Compared to heuristic fuzzy rules, fuzzy rules generated from data are able to extract more profound knowledge for more complex systems. This book presents a number of approaches to the generation of fuzzy rules from data, ranging from the direct fuzzy inference based to neural net works and evolutionary algorithms based fuzzy rule generation. Besides the approximation accuracy, special attention has been paid to the interpretabil ity of the extracted fuzzy rules. In other words, the fuzzy rules generated from data are supposed to be as comprehensible to human beings as those generated from human heuristics. To this end, many aspects of interpretabil ity of fuzzy systems have been discussed, which must be taken into account in the data-driven fuzzy rule generation. In this way, fuzzy rules generated from data are intelligible to human users and therefore, knowledge about unknown systems can be extracted.Physica Verlag, Tiergartenstr. 17, 69121 Heidelberg 288 pp. Englisch.
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
EUR 169,19
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Añadir al carritoCondición: New. Using neural networks and evolutionary algorithms, this book presents a variety of recently developed methods for generating fuzzy rules from data. It considers knowledge incorporation into neural and evolutionary systems and knowledge extraction from data with fuzzy logic. Series: Studies in Fuzziness and Soft Computing. Num Pages: 272 pages, 228 black & white illustrations, 10 black & white tables, biography. BIC Classification: PBWX; UMB; UYQ. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 233 x 155 x 17. Weight in Grams: 586. . 2003. 2003rd Edition. Hardcover. . . . . Books ship from the US and Ireland.
Publicado por Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Heidelberg, 2011
ISBN 10: 3790825204 ISBN 13: 9783790825206
Idioma: Inglés
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 187,81
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Añadir al carritoPaperback. Condición: new. Paperback. This book presents a variety of recently developed methods for generating fuzzy rules from data with the help of neural networks and evolutionary algorithms. Special efforts have been put on dealing with knowledge incorporation into neural and evolutionary systems and knowledge extraction from data with the help of fuzzy logic. On the one hand, knowledge that is understandable to human beings can be extracted from data using evolutionary and learning methods by maintaining the interpretability of the generated fuzzy rules. On the other hand, a priori knowledge like expert knowledge and human preferences can be incorporated into evolution and learning, taking advantage of the knowledge representation capability of fuzzy rule systems and fuzzy preference models. Several engineering application examples in the fields of intelligent vehicle systems, process modeling and control and robotics are presented. Compared to heuristic fuzzy rules, fuzzy rules generated from data are able to extract more profound knowledge for more complex systems. This book presents a number of approaches to the generation of fuzzy rules from data, ranging from the direct fuzzy inference based to neural net works and evolutionary algorithms based fuzzy rule generation. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Librería: moluna, Greven, Alemania
EUR 92,27
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Añadir al carritoGebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Fuzzy rule systems have found a wide range of applications in many fields of science and technology. Traditionally, fuzzy rules are generated from human expert knowledge or human heuristics for relatively simple systems. In the last few years, data-driven f.
Librería: moluna, Greven, Alemania
EUR 92,27
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Fuzzy rule systems have found a wide range of applications in many fields of science and technology. Traditionally, fuzzy rules are generated from human expert knowledge or human heuristics for relatively simple systems. In the last few years, data-driven f.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 147,86
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Añadir al carritoCondición: New. Print on Demand pp. 284 170 Illus.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 150,25
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 284.
Publicado por Physica-Verlag, Physica-Verlag HD, Physica Dez 2011, 2011
ISBN 10: 3790825204 ISBN 13: 9783790825206
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 139,09
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Fuzzy rule systems have found a wide range of applications in many fields of science and technology. Traditionally, fuzzy rules are generated from human expert knowledge or human heuristics for relatively simple systems. In the last few years, data-driven fuzzy rule generation has been very active. Compared to heuristic fuzzy rules, fuzzy rules generated from data are able to extract more profound knowledge for more complex systems. This book presents a number of approaches to the generation of fuzzy rules from data, ranging from the direct fuzzy inference based to neural net works and evolutionary algorithms based fuzzy rule generation. Besides the approximation accuracy, special attention has been paid to the interpretabil ity of the extracted fuzzy rules. In other words, the fuzzy rules generated from data are supposed to be as comprehensible to human beings as those generated from human heuristics. To this end, many aspects of interpretabil ity of fuzzy systems have been discussed, which must be taken into account in the data-driven fuzzy rule generation. In this way, fuzzy rules generated from data are intelligible to human users and therefore, knowledge about unknown systems can be extracted. 272 pp. Englisch.
Publicado por Physica-Verlag HD Dez 2011, 2011
ISBN 10: 3790825204 ISBN 13: 9783790825206
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 106,99
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Fuzzy rule systems have found a wide range of applications in many fields of science and technology. Traditionally, fuzzy rules are generated from human expert knowledge or human heuristics for relatively simple systems. In the last few years, data-driven fuzzy rule generation has been very active. Compared to heuristic fuzzy rules, fuzzy rules generated from data are able to extract more profound knowledge for more complex systems. This book presents a number of approaches to the generation of fuzzy rules from data, ranging from the direct fuzzy inference based to neural net works and evolutionary algorithms based fuzzy rule generation. Besides the approximation accuracy, special attention has been paid to the interpretabil ity of the extracted fuzzy rules. In other words, the fuzzy rules generated from data are supposed to be as comprehensible to human beings as those generated from human heuristics. To this end, many aspects of interpretabil ity of fuzzy systems have been discussed, which must be taken into account in the data-driven fuzzy rule generation. In this way, fuzzy rules generated from data are intelligible to human users and therefore, knowledge about unknown systems can be extracted.Physica Verlag, Tiergartenstr. 17, 69121 Heidelberg 284 pp. Englisch.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 106,99
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Fuzzy rule systems have found a wide range of applications in many fields of science and technology. Traditionally, fuzzy rules are generated from human expert knowledge or human heuristics for relatively simple systems. In the last few years, data-driven fuzzy rule generation has been very active. Compared to heuristic fuzzy rules, fuzzy rules generated from data are able to extract more profound knowledge for more complex systems. This book presents a number of approaches to the generation of fuzzy rules from data, ranging from the direct fuzzy inference based to neural net works and evolutionary algorithms based fuzzy rule generation. Besides the approximation accuracy, special attention has been paid to the interpretabil ity of the extracted fuzzy rules. In other words, the fuzzy rules generated from data are supposed to be as comprehensible to human beings as those generated from human heuristics. To this end, many aspects of interpretabil ity of fuzzy systems have been discussed, which must be taken into account in the data-driven fuzzy rule generation. In this way, fuzzy rules generated from data are intelligible to human users and therefore, knowledge about unknown systems can be extracted.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 106,99
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Añadir al carritoBuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Fuzzy rule systems have found a wide range of applications in many fields of science and technology. Traditionally, fuzzy rules are generated from human expert knowledge or human heuristics for relatively simple systems. In the last few years, data-driven fuzzy rule generation has been very active. Compared to heuristic fuzzy rules, fuzzy rules generated from data are able to extract more profound knowledge for more complex systems. This book presents a number of approaches to the generation of fuzzy rules from data, ranging from the direct fuzzy inference based to neural net works and evolutionary algorithms based fuzzy rule generation. Besides the approximation accuracy, special attention has been paid to the interpretabil ity of the extracted fuzzy rules. In other words, the fuzzy rules generated from data are supposed to be as comprehensible to human beings as those generated from human heuristics. To this end, many aspects of interpretabil ity of fuzzy systems have been discussed, which must be taken into account in the data-driven fuzzy rule generation. In this way, fuzzy rules generated from data are intelligible to human users and therefore, knowledge about unknown systems can be extracted.