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Published by Springer, Berlin|Springer Nature Singapore|Springer, 2021
ISBN 10: 9811557748 ISBN 13: 9789811557743
Language: English
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Published by Springer Nature Singapore, Springer Nature Singapore, 2021
ISBN 10: 9811557748 ISBN 13: 9789811557743
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book highlights cutting-edge applications of machine learning techniquesfor disaster management by monitoring, analyzing, and forecasting hydro-meteorological variables.Predictive modelling is a consolidated discipline used to forewarn the possibility of natural hazards. In this book, experts from numerical weather forecast, meteorology, hydrology, engineering, agriculture, economics, and disaster policy-making contribute towards an interdisciplinary framework to construct potent models for hazard risk mitigation. The book will help advance the state of knowledge of artificial intelligence in decision systems to aid disaster management and policy-making. This book can be a useful reference for graduate student, academics, practicing scientists and professionals of disaster management, artificial intelligence, and environmental sciences.
Published by Springer Nature Singapore, Springer Nature Singapore, 2020
ISBN 10: 9811557713 ISBN 13: 9789811557712
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Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book highlights cutting-edge applications of machine learning techniquesfor disaster management by monitoring, analyzing, and forecasting hydro-meteorological variables.Predictive modelling is a consolidated discipline used to forewarn the possibility of natural hazards. In this book, experts from numerical weather forecast, meteorology, hydrology, engineering, agriculture, economics, and disaster policy-making contribute towards an interdisciplinary framework to construct potent models for hazard risk mitigation. The book will help advance the state of knowledge of artificial intelligence in decision systems to aid disaster management and policy-making. This book can be a useful reference for graduate student, academics, practicing scientists and professionals of disaster management, artificial intelligence, and environmental sciences.
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Published by Springer Verlag, Singapore, Singapore, 2020
ISBN 10: 9811557713 ISBN 13: 9789811557712
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Add to basketHardcover. Condition: new. Hardcover. This book highlights cutting-edge applications of machine learning techniques for disaster management by monitoring, analyzing, and forecasting hydro-meteorological variables. Predictive modelling is a consolidated discipline used to forewarn the possibility of natural hazards. In this book, experts from numerical weather forecast, meteorology, hydrology, engineering, agriculture, economics, and disaster policy-making contribute towards an interdisciplinary framework to construct potent models for hazard risk mitigation. The book will help advance the state of knowledge of artificial intelligence in decision systems to aid disaster management and policy-making. This book can be a useful reference for graduate student, academics, practicing scientists and professionals of disaster management, artificial intelligence, and environmental sciences. This book highlights cutting-edge applications of machine learning techniques for disaster management by monitoring, analyzing, and forecasting hydro-meteorological variables. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Springer Nature Singapore, Springer Nature Singapore Jul 2020, 2020
ISBN 10: 9811557713 ISBN 13: 9789811557712
Language: English
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Add to basketBuch. Condition: Neu. Neuware -This book highlights cutting-edge applications of machine learning techniques for disaster management by monitoring, analyzing, and forecasting hydro-meteorological variables. Predictive modelling is a consolidated discipline used to forewarn the possibility of natural hazards. In this book, experts from numerical weather forecast, meteorology, hydrology, engineering, agriculture, economics, and disaster policy-making contribute towards an interdisciplinary framework to construct potent models for hazard risk mitigation. The book will help advance the state of knowledge of artificial intelligence in decision systems to aid disaster management and policy-making. This book can be a useful reference for graduate student, academics, practicing scientists and professionals of disaster management, artificial intelligence, and environmental sciences.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 492 pp. Englisch.
Published by Springer Nature Singapore, Springer Nature Singapore Jul 2021, 2021
ISBN 10: 9811557748 ISBN 13: 9789811557743
Language: English
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Published by Springer Verlag, Singapore, Singapore, 2021
ISBN 10: 9811557748 ISBN 13: 9789811557743
Language: English
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Published by Springer Verlag, Singapore, Singapore, 2021
ISBN 10: 9811557748 ISBN 13: 9789811557743
Language: English
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Add to basketPaperback. Condition: new. Paperback. This book highlights cutting-edge applications of machine learning techniques for disaster management by monitoring, analyzing, and forecasting hydro-meteorological variables. Predictive modelling is a consolidated discipline used to forewarn the possibility of natural hazards. In this book, experts from numerical weather forecast, meteorology, hydrology, engineering, agriculture, economics, and disaster policy-making contribute towards an interdisciplinary framework to construct potent models for hazard risk mitigation. The book will help advance the state of knowledge of artificial intelligence in decision systems to aid disaster management and policy-making. This book can be a useful reference for graduate student, academics, practicing scientists and professionals of disaster management, artificial intelligence, and environmental sciences. This book highlights cutting-edge applications of machine learning techniques for disaster management by monitoring, analyzing, and forecasting hydro-meteorological variables. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Published by Springer Verlag, Singapore, Singapore, 2020
ISBN 10: 9811557713 ISBN 13: 9789811557712
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents novel applications of artificial neural networks to design practical alert systems for natural hazardsOffers concise theories and case studies on advanced data analytics for real-life decision support systems.
Published by Springer Nature Singapore Jul 2021, 2021
ISBN 10: 9811557748 ISBN 13: 9789811557743
Language: English
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book highlights cutting-edge applications of machine learning techniquesfor disaster management by monitoring, analyzing, and forecasting hydro-meteorological variables.Predictive modelling is a consolidated discipline used to forewarn the possibility of natural hazards. In this book, experts from numerical weather forecast, meteorology, hydrology, engineering, agriculture, economics, and disaster policy-making contribute towards an interdisciplinary framework to construct potent models for hazard risk mitigation. The book will help advance the state of knowledge of artificial intelligence in decision systems to aid disaster management and policy-making. This book can be a useful reference for graduate student, academics, practicing scientists and professionals of disaster management, artificial intelligence, and environmental sciences. 492 pp. Englisch.
Published by Springer Nature Singapore Jul 2020, 2020
ISBN 10: 9811557713 ISBN 13: 9789811557712
Language: English
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Add to basketBuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book highlights cutting-edge applications of machine learning techniquesfor disaster management by monitoring, analyzing, and forecasting hydro-meteorological variables.Predictive modelling is a consolidated discipline used to forewarn the possibility of natural hazards. In this book, experts from numerical weather forecast, meteorology, hydrology, engineering, agriculture, economics, and disaster policy-making contribute towards an interdisciplinary framework to construct potent models for hazard risk mitigation. The book will help advance the state of knowledge of artificial intelligence in decision systems to aid disaster management and policy-making. This book can be a useful reference for graduate student, academics, practicing scientists and professionals of disaster management, artificial intelligence, and environmental sciences. 492 pp. Englisch.