Advanced data-driven approaches for modelling and classification: with applications to automotive engine fault detection and polymer extrusion control - Brossura
Sinossi
In this book, the Fast Recursive Algorithm (FRA) and Two-Stage Selection (TSS) methods proposed by Prof. Li and Prof. Irwin have been improved to integrate Bayesian regularisation to prevent over-fitting and leave-one-out cross validation for automatic model construction. To further enhance model generalization capability, some heuristic methods were also embedded in the two-stage selection to optimize the non-linear parameters involved in subset model construction. These include Particle Swarm Optimization (PSO), Defferential Evolution (DE), and Extreme Learning Machine (ELM). The effectiveness and efficiency of all these advanced methods have been confirmed on both well-known benchmarks and real world data sets from automotive engine and polymer extrusion applications.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sull?autore
Dr Jing Deng received his B.Sc.degree from National University of Defence Technology, Hunan, China, in 2005, the M.Sc.degrees from the Shanghai University, Shanghai, China, in 2007, and the Ph.D. degree from the Intelligent Systems and Control(ISAC) Group at Queen’s University Belfast,UK in 2011. From then, he worked as a research Fellow at QUB.
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Advanced data-driven approaches for modelling and classification
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LAP LAMBERT Academic Publishing Nov 2012, 2012
ISBN 10: 3659301418
ISBN 13: 9783659301414
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, the Fast Recursive Algorithm (FRA) and Two-Stage Selection (TSS) methods proposed by Prof. Li and Prof. Irwin have been improved to integrate Bayesian regularisation to prevent over-fitting and leave-one-out cross validation for automatic model construction. To further enhance model generalization capability, some heuristic methods were also embedded in the two-stage selection to optimize the non-linear parameters involved in subset model construction. These include Particle Swarm Optimization (PSO), Defferential Evolution (DE), and Extreme Learning Machine (ELM). The effectiveness and efficiency of all these advanced methods have been confirmed on both well-known benchmarks and real world data sets from automotive engine and polymer extrusion applications. 160 pp. Englisch. Codice articolo 9783659301414
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Advanced data-driven approaches for modelling and classification
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LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659301418
ISBN 13: 9783659301414
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Deng JingDr Jing Deng received his B.Sc.degree from National University of Defence Technology, Hunan, China, in 2005, the M.Sc.degrees from the Shanghai University, Shanghai, China, in 2007, and the Ph.D. degree from the Intelligent . Codice articolo 5146901
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Advanced data-driven approaches for modelling and classification
Editore:
LAP LAMBERT Academic Publishing Nov 2012, 2012
ISBN 10: 3659301418
ISBN 13: 9783659301414
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book, the Fast Recursive Algorithm (FRA) and Two-Stage Selection (TSS) methods proposed by Prof. Li and Prof. Irwin have been improved to integrate Bayesian regularisation to prevent over-fitting and leave-one-out cross validation for automatic model construction. To further enhance model generalization capability, some heuristic methods were also embedded in the two-stage selection to optimize the non-linear parameters involved in subset model construction. These include Particle Swarm Optimization (PSO), Defferential Evolution (DE), and Extreme Learning Machine (ELM). The effectiveness and efficiency of all these advanced methods have been confirmed on both well-known benchmarks and real world data sets from automotive engine and polymer extrusion applications.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 160 pp. Englisch. Codice articolo 9783659301414
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Advanced data-driven approaches for modelling and classification : with applications to automotive engine fault detection and polymer extrusion control
Editore:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659301418
ISBN 13: 9783659301414
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, the Fast Recursive Algorithm (FRA) and Two-Stage Selection (TSS) methods proposed by Prof. Li and Prof. Irwin have been improved to integrate Bayesian regularisation to prevent over-fitting and leave-one-out cross validation for automatic model construction. To further enhance model generalization capability, some heuristic methods were also embedded in the two-stage selection to optimize the non-linear parameters involved in subset model construction. These include Particle Swarm Optimization (PSO), Defferential Evolution (DE), and Extreme Learning Machine (ELM). The effectiveness and efficiency of all these advanced methods have been confirmed on both well-known benchmarks and real world data sets from automotive engine and polymer extrusion applications. Codice articolo 9783659301414
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Advanced data-driven approaches for modelling and classification | with applications to automotive engine fault detection and polymer extrusion control
Editore:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659301418
ISBN 13: 9783659301414
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Taschenbuch. Condizione: Neu. Advanced data-driven approaches for modelling and classification | with applications to automotive engine fault detection and polymer extrusion control | Jing Deng | Taschenbuch | 160 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783659301414 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 106168407
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Advanced data-driven approaches for modelling and classification: with applications to automotive engine fault detection and polymer extrusion control
Editore:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659301418
ISBN 13: 9783659301414
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