Intelligent Data Analytics for Decision-Support Systems in Hazard Mitigation
Theory and Practice of Hazard Mitigation
Series: Springer Transactions in Civil and Environmental Engineering;
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Product details:
- Edition number 1st ed. 2021
- Publisher Springer Nature Singapore
- Date of Publication 31 July 2021
- Number of Volumes 1 pieces, Book
- ISBN 9789811557743
- Binding Paperback
- See also 9789811557712
- No. of pages469 pages
- Size 235x155 mm
- Weight 747 g
- Language English
- Illustrations XX, 469 p. 225 illus., 205 illus. in color. Illustrations, black & white 175
Categories
Long 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.
MoreTable of Contents:
Chapter 1: Drought Index Prediction using Data Intelligent Analytic Models: A Review.- Chapter 2: Bayesian Markov Chain Monte Carlo based copulas: Factoring the Role of Large-scale Climate Indices in Monthly Flood Prediction.- Chapter 3: Gaussian Naive Bayes Classification Algorithm for Drought and Flood Risk Reduction.- Chapter 4: Hydrological Drought Investigation using Streamflow Drought Index.- Chapter 5: Intelligent Data Analytics Approaches for Predicting Dissolved Oxygen Concentration in River: Extremely Randomized Tree Vs Random Forest, MLPNN and MLR.- Chapter 6: Evolving Connectionist Systems versus Neuro-Fuzzy System for Estimating Total Dissolved Gas at Forebay and Tailwater of Dams Reservoirs.- Chapter 7: Modulation of Tropical Cyclone Genesis by Madden-Julian Oscillation in the Southern Hemisphere.- Chapter 8: Intelligent Data Analytics for Time-series, Trend Analysis and Drought Indices Comparison.- Chapter 9: Conjunction Model Design for Intermittent Streamflow Forecasts: Extreme Learning Machine with Discrete Wavelet Transform.- Chapter 10: Systematic Integration of Artificial Intelligence Towards Evaluating Response of Materials and Structures in Extreme Conditions.
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