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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. 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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