Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 100,54
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Da: Books Puddle, New York, NY, U.S.A.
EUR 120,50
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Aggiungi al carrelloCondizione: New. pp. 262.
Da: Majestic Books, Hounslow, Regno Unito
EUR 122,07
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Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 121,70
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 127,03
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Aggiungi al carrelloCondizione: New. pp. 262.
Editore: Elsevier Science Publishing Co Inc, 2020
ISBN 10: 0128193654 ISBN 13: 9780128193655
Lingua: Inglese
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 148,67
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Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days. 520.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 171,16
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 161,89
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 186,88
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Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 267,43
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Aggiungi al carrellopaperback. Condizione: New. New. book.
Editore: Elsevier Science & Technology|Elsevier, 2020
ISBN 10: 0128193654 ISBN 13: 9780128193655
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 128,97
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance .
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 118,91
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Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Editore: Elsevier Science & Technology, Elsevier, 2020
ISBN 10: 0128193654 ISBN 13: 9780128193655
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 132,00
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches - such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches - to develop more sophisticated and efficient monitoring techniques. Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems. Englisch.
Da: Revaluation Books, Exeter, Regno Unito
EUR 138,09
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Aggiungi al carrelloPaperback. Condizione: Brand New. 262 pages. 8.75x5.75x1.00 inches. In Stock. This item is printed on demand.
Editore: Elsevier Science & Technology, Elsevier, 2020
ISBN 10: 0128193654 ISBN 13: 9780128193655
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 145,00
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches - such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches - to develop more sophisticated and efficient monitoring techniques. Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems.