Isis didier lins (9 risultati)

Support Vector Machines and Particle Swarm Optimization
Mrcio Das Chagas Moura Enrique Lpez Droguett Isis Didier Lins
Lingua: Inglese
Editore: VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG 2010
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 79,23
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Condizione: New. pp. 92.

Support Vector Machines and Particle Swarm Optimization
Isis Didier Lins|Márcio das Chagas Moura|Enrique López Droguett
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Da: moluna, Greven, Germaniamoluna
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EUR 41,05
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Condizione: New.

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Da: preigu, Osnabrück, Germaniapreigu
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EUR 43,30
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Taschenbuch. Condizione: Neu. Support Vector Machines and Particle Swarm Optimization | Applications to Reliability Prediction | Isis Didier Lins (u. a.) | Taschenbuch | 92 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838319407 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19…, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

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Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
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EUR 120,62
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Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

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- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 49,00
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Reliability is a critical indicator of organizations' performance in face of market competition, since it contributes to production regularity. Its prediction is of great interest as it may anticipate trends of system failures and…thus enable maintenance actions. The consideration of all aspects that influence system reliability may render its modeling very complex and learning methods such as Support Vector Machines (SVMs) emerge as alternative prediction tools: previous knowledge about the function or process that maps input variables into output is not required. However, SVM performance is affected by parameters from the related learning problem. Suitable values for them are chosen by means of Particle Swarm Optimization (PSO), a probabilistic approach based on the behavior of organisms that move in groups. Thus, a PSO+SVM methodology is proposed to handle reliability prediction problems. It is used to solve application examples based on time series data and also involving data collected from oil production wells. The results indicate that PSO+SVM is able to provide competitive or even more accurate reliability predictions when compared, for example, to Neural Networks (NNs). 92 pp. Englisch.

Support Vector Machines and Particle Swarm Optimization
Das Chagas Moura Mrcio Lpez Droguett Enrique Lins Isis Didier
Lingua: Inglese
Editore: VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG 2010
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- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 79,12
EUR 7,54 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand pp. 92 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Support Vector Machines and Particle Swarm Optimization
Das Chagas Moura Mrcio Lpez Droguett Enrique Lins Isis Didier
Lingua: Inglese
Editore: VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG 2010
- Brossura
- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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EUR 78,93
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND pp. 92.

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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 49,00
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Reliability is a critical indicator of organizations'' performance in face of market competition, since it contributes to production regularity. Its prediction is of great interest as it may anticipate trends of system failures and thu…s enable maintenance actions. The consideration of all aspects that influence system reliability may render its modeling very complex and learning methods such as Support Vector Machines (SVMs) emerge as alternative prediction tools: previous knowledge about the function or process that maps input variables into output is not required. However, SVM performance is affected by parameters from the related learning problem. Suitable values for them are chosen by means of Particle Swarm Optimization (PSO), a probabilistic approach based on the behavior of organisms that move in groups. Thus, a PSO+SVM methodology is proposed to handle reliability prediction problems. It is used to solve application examples based on time series data and also involving data collected from oil production wells. The results indicate that PSO+SVM is able to provide competitive or even more accurate reliability predictions when compared, for example, to Neural Networks (NNs).VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 92 pp. Englisch.

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- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 49,00
EUR 60,78 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Reliability is a critical indicator of organizations' performance in face of market competition, since it contributes to production regularity. Its prediction is of great interest as it may anticipate trends of system failures and thus…enable maintenance actions. The consideration of all aspects that influence system reliability may render its modeling very complex and learning methods such as Support Vector Machines (SVMs) emerge as alternative prediction tools: previous knowledge about the function or process that maps input variables into output is not required. However, SVM performance is affected by parameters from the related learning problem. Suitable values for them are chosen by means of Particle Swarm Optimization (PSO), a probabilistic approach based on the behavior of organisms that move in groups. Thus, a PSO+SVM methodology is proposed to handle reliability prediction problems. It is used to solve application examples based on time series data and also involving data collected from oil production wells. The results indicate that PSO+SVM is able to provide competitive or even more accurate reliability predictions when compared, for example, to Neural Networks (NNs).