Sinossi
This book is proposing a hybrid algorithm of two fuzzy genetic-based machine learning approaches - Michigan and Pittsburgh - for designing fuzzy rule-based classification systems. The search ability of each approach is examined to efficiently find fuzzy rule-based systems with high classification accuracy. These two approaches are combined into a single hybrid algorithm. The generalization ability of fuzzy rule-based classification systems, designed by the proposed hybrid algorithm is examined on real data sets. Experimental results show that the hybrid algorithm has higher search ability within a population of individual rules and within a population of rule sets.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
L'autore
Dr. Lamiaa H. Ahmed is a Lecturer of Computer Science at Modern Academy in Maadi, Cairo, Egypt. Computational Intelligence, Evolutionary Programming, Membrane Computing, Fuzzy Logic, Organic Computing and Java programming language are areas of interest.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Risultati della ricerca per Evolutionary Machine Learning in Linguistic Knowledge...
Immagini fornite dal venditore
Evolutionary Machine Learning in Linguistic Knowledge Extraction
Editore:
LAP LAMBERT Academic Publishing Mai 2016, 2016
ISBN 10: 3659891037
ISBN 13: 9783659891038
Nuovo
Taschenbuch
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is proposing a hybrid algorithm of two fuzzy genetic-based machine learning approaches - Michigan and Pittsburgh - for designing fuzzy rule-based classification systems. The search ability of each approach is examined to efficiently find fuzzy rule-based systems with high classification accuracy. These two approaches are combined into a single hybrid algorithm. The generalization ability of fuzzy rule-based classification systems, designed by the proposed hybrid algorithm is examined on real data sets. Experimental results show that the hybrid algorithm has higher search ability within a population of individual rules and within a population of rule sets. 140 pp. Englisch. Codice articolo 9783659891038
Compra nuovo
EUR 61,90
Spedizione EUR 23,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 2 disponibili
Immagini fornite dal venditore
Evolutionary Machine Learning in Linguistic Knowledge Extraction
Editore:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659891037
ISBN 13: 9783659891038
Nuovo
Brossura
Da: moluna, Greven, Germania
Valutazione del venditore 4 su 5 stelle
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ahmed LamiaaDr. Lamiaa H. Ahmed is a Lecturer of Computer Science at Modern Academy in Maadi, Cairo, Egypt. Computational Intelligence, Evolutionary Programming, Membrane Computing, Fuzzy Logic, Organic Computing and Java programming. Codice articolo 158248679
Compra nuovo
EUR 50,66
Spedizione EUR 48,99
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
Evolutionary Machine Learning in Linguistic Knowledge Extraction
Editore:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659891037
ISBN 13: 9783659891038
Nuovo
Paperback
Da: Revaluation Books, Exeter, Regno Unito
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: Brand New. 140 pages. 8.66x5.91x0.32 inches. In Stock. Codice articolo 3659891037
Compra nuovo
EUR 106,18
Spedizione EUR 11,44
Spedito da Regno Unito a U.S.A.
Spedito da Regno Unito a U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
Evolutionary Machine Learning in Linguistic Knowledge Extraction
Editore:
LAP LAMBERT Academic Publishing Mai 2016, 2016
ISBN 10: 3659891037
ISBN 13: 9783659891038
Nuovo
Taschenbuch
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is proposing a hybrid algorithm of two fuzzy genetic-based machine learning approaches - Michigan and Pittsburgh - for designing fuzzy rule-based classification systems. The search ability of each approach is examined to efficiently find fuzzy rule-based systems with high classification accuracy. These two approaches are combined into a single hybrid algorithm. The generalization ability of fuzzy rule-based classification systems, designed by the proposed hybrid algorithm is examined on real data sets. Experimental results show that the hybrid algorithm has higher search ability within a population of individual rules and within a population of rule sets.Books on Demand GmbH, Überseering 33, 22297 Hamburg 140 pp. Englisch. Codice articolo 9783659891038
Compra nuovo
EUR 61,90
Spedizione EUR 60,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
Evolutionary Machine Learning in Linguistic Knowledge Extraction
Editore:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659891037
ISBN 13: 9783659891038
Nuovo
Taschenbuch
Da: preigu, Osnabrück, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. Evolutionary Machine Learning in Linguistic Knowledge Extraction | Lamiaa Ahmed (u. a.) | Taschenbuch | 140 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659891038 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand. Codice articolo 103715507
Compra nuovo
EUR 52,60
Spedizione EUR 70,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 5 disponibili
Immagini fornite dal venditore
Evolutionary Machine Learning in Linguistic Knowledge Extraction
Editore:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659891037
ISBN 13: 9783659891038
Nuovo
Taschenbuch
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book is proposing a hybrid algorithm of two fuzzy genetic-based machine learning approaches - Michigan and Pittsburgh - for designing fuzzy rule-based classification systems. The search ability of each approach is examined to efficiently find fuzzy rule-based systems with high classification accuracy. These two approaches are combined into a single hybrid algorithm. The generalization ability of fuzzy rule-based classification systems, designed by the proposed hybrid algorithm is examined on real data sets. Experimental results show that the hybrid algorithm has higher search ability within a population of individual rules and within a population of rule sets. Codice articolo 9783659891038
Compra nuovo
EUR 61,90
Spedizione EUR 61,14
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 1 disponibili