Support Vector Machines and Particle Swarm Optimization: Applications to Reliability Prediction - Softcover

Lins, Isis Didier; Das, Márcio; López, Enrique

 
9783838319407: Support Vector Machines and Particle Swarm Optimization: Applications to Reliability Prediction
Softcover
ISBN 10: 3838319400 ISBN 13: 9783838319407
Verlag: LAP Lambert Academic Publishing, 2010

Inhaltsangabe

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).

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Über die Autorin bzw. den Autor

Isis Lins: researcher at the Center of Risk Analysis and Environmental Modeling (CEERMA); MSc in Production Engineering from Federal University of Pernambuco (UFPE), 2010. Márcio Moura: researcher at CEERMA; PhD in Production Engineering from UFPE, 2009. Enrique Droguett: professor at the Production Engineering Department (UFPE); CEERMA''s director.

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Verlag
LAP Lambert Academic Publishing
Erscheinungsdatum
2010
Sprache
Englisch
ISBN 10 
3838319400
ISBN 13 
9783838319407
Einband
Taschenbuch
Anzahl der Seiten
92
Kontakt zum Hersteller
Nicht verfügbar
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