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Hardcover. Zustand: new. Hardcover. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Verlag: Royal Society of Chemistry, GB, 2023
ISBN 10: 1839165634 ISBN 13: 9781839165634
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Verlag: Royal Society of Chemistry, 2023
ISBN 10: 1839165634 ISBN 13: 9781839165634
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In den WarenkorbHardback. Zustand: 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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Buch. Zustand: 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.
Verlag: Royal Society of Chemistry, Cambridge, 2023
ISBN 10: 1839165634 ISBN 13: 9781839165634
Sprache: Englisch
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Hardcover. Zustand: new. Hardcover. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.