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Ajouter au panierPaperback / softback. Etat : New. New copy - Usually dispatched within 4 working days.
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Ajouter au panierPaperback. Etat : Brand New. 260 pages. 9.18x6.12x9.21 inches. In Stock.
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Ajouter au panierHardcover. Etat : Brand New. 280 pages. 9.19x6.13x0.78 inches. In Stock.
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Ajouter au panierPAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The text discusses the latest data-driven, physics-based, and hybrid approaches employed in each stage of industrial prognostics and reliability estimation. It will be a useful text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Ajouter au panierBuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The text discusses the latest data-driven, physics-based, and hybrid approaches employed in each stage of industrial prognostics and reliability estimation. It will be a useful text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, electrical engineering, and computer science.The bookDiscusses basic as well as advance research in the field of prognosticsExplores integration of data collection, fault detection, degradation modeling and reliability prediction in one volumeCovers prognostics and health management (PHM) of engineering systemsDiscusses latest approaches in the field of prognostics based on machine learningThe text deals with tools and techniques used to predict/ extrapolate/ forecast the process behavior, based on current health state assessment and future operating conditions with the help of Machine learning. It will serve as a useful reference text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, manufacturing science, electrical engineering, and computer science. 262 pp. Englisch.
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Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Gunjan Soni did his B.E. from University of Rajasthan, M.Tech from IIT, Delhi and PhD. From Birla Institute of Technology and Science, Pilani in 2012. He is presently working as an Assistant Professor with Department of Mechanical Engineering, Malaviya N.
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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Ajouter au panierHRD. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
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Ajouter au panierHRD. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
EUR 171,54
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Ajouter au panierBuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The text discusses the latest data-driven, physics-based, and hybrid approaches employed in each stage of industrial prognostics and reliability estimation. It will be a useful text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, electrical engineering, and computer science.The bookDiscusses basic as well as advance research in the field of prognosticsExplores integration of data collection, fault detection, degradation modeling and reliability prediction in one volumeCovers prognostics and health management (PHM) of engineering systemsDiscusses latest approaches in the field of prognostics based on machine learningThe text deals with tools and techniques used to predict/ extrapolate/ forecast the process behavior, based on current health state assessment and future operating conditions with the help of Machine learning. It will serve as a useful reference text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, manufacturing science, electrical engineering, and computer science.