Intelligent Data Analytics for Decision-Support Systems in Hazard Mitigation - Theory and Practice of Hazard Mitigation (Hardcover, 1st ed. 2021)


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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Product Description

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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Product Details

General

Imprint

Springer Verlag, Singapore

Country of origin

Singapore

Series

Springer Transactions in Civil and Environmental Engineering

Release date

July 2020

Availability

Expected to ship within 12 - 17 working days

First published

2021

Editors

, , ,

Dimensions

235 x 155mm (L x W)

Format

Hardcover

Pages

469

Edition

1st ed. 2021

ISBN-13

978-981-15-5771-2

Barcode

9789811557712

Categories

LSN

981-15-5771-3



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