Lingua: Inglese
Editore: Royal Society of Chemistry, 2023
ISBN 10: 1839165634 ISBN 13: 9781839165634
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Lingua: Inglese
Editore: Royal Society of Chemistry, 2023
ISBN 10: 1839165634 ISBN 13: 9781839165634
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Lingua: Inglese
Editore: Royal Society of Chemistry, 2023
ISBN 10: 1839165634 ISBN 13: 9781839165634
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Lingua: Inglese
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ISBN 10: 1839165634 ISBN 13: 9781839165634
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ISBN 10: 1839165634 ISBN 13: 9781839165634
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Lingua: Inglese
Editore: Royal Society of Chemistry, GB, 2023
ISBN 10: 1839165634 ISBN 13: 9781839165634
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Aggiungi al carrelloHardback. Condizione: New. Over the last decade, there has been a significant shift from traditional mechanistic and empirical modelling into statistical and data-driven modelling for applications in reaction engineering. In particular, the integration of machine learning and first-principle models has demonstrated significant potential and success in the discovery of (bio)chemical kinetics, prediction and optimisation of complex reactions, and scale-up of industrial reactors. Summarising the latest research and illustrating the current frontiers in applications of hybrid modelling for chemical and biochemical reaction engineering, Machine Learning and Hybrid Modelling for Reaction Engineering fills a gap in the methodology development of hybrid models. With a systematic explanation of the fundamental theory of hybrid model construction, time-varying parameter estimation, model structure identification and uncertainty analysis, this book is a great resource for both chemical engineers looking to use the latest computational techniques in their research and computational chemists interested in new applications for their work.
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Lingua: Inglese
Editore: Royal Society of Chemistry, 2023
ISBN 10: 1839165634 ISBN 13: 9781839165634
Da: Revaluation Books, Exeter, Regno Unito
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Lingua: Inglese
Editore: Royal Society of Chemistry, GB, 2023
ISBN 10: 1839165634 ISBN 13: 9781839165634
Da: Rarewaves.com UK, London, Regno Unito
EUR 290,98
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Aggiungi al carrelloHardback. Condizione: New. Over the last decade, there has been a significant shift from traditional mechanistic and empirical modelling into statistical and data-driven modelling for applications in reaction engineering. In particular, the integration of machine learning and first-principle models has demonstrated significant potential and success in the discovery of (bio)chemical kinetics, prediction and optimisation of complex reactions, and scale-up of industrial reactors. Summarising the latest research and illustrating the current frontiers in applications of hybrid modelling for chemical and biochemical reaction engineering, Machine Learning and Hybrid Modelling for Reaction Engineering fills a gap in the methodology development of hybrid models. With a systematic explanation of the fundamental theory of hybrid model construction, time-varying parameter estimation, model structure identification and uncertainty analysis, this book is a great resource for both chemical engineers looking to use the latest computational techniques in their research and computational chemists interested in new applications for their work.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 292,42
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware - Machine Learning and Hybrid Modelling for Reaction Engineering summarises latest research and fills a gap in methodology development of hybrid models for reaction engineering applications.