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Intelligent Data Analytics for Decision-Support Systems in Hazard Mitigation

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Cover of 'Intelligent Data Analytics for Decision-Support Systems in Hazard Mitigation'

Table of Contents

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    Book Overview
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    Chapter 1 Drought Index Prediction Using Data Intelligent Analytic Models: A Review
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    Chapter 2 Bayesian Markov Chain Monte Carlo-Based Copulas: Factoring the Role of Large-Scale Climate Indices in Monthly Flood Prediction
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    Chapter 3 Gaussian Naïve Bayes Classification Algorithm for Drought and Flood Risk Reduction
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    Chapter 4 Hydrological Drought Investigation Using Streamflow Drought Index
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    Chapter 5 Intelligent Data Analytics Approaches for Predicting Dissolved Oxygen Concentration in River: Extremely Randomized Tree Versus Random Forest, MLPNN and MLR
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    Chapter 6 Evolving Connectionist Systems Versus Neuro-Fuzzy System for Estimating Total Dissolved Gas at Forebay and Tailwater of Dams Reservoirs
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    Chapter 7 Modulation of Tropical Cyclone Genesis by Madden–Julian Oscillation in the Southern Hemisphere
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    Chapter 8 Intelligent Data Analytics for Time Series, Trend Analysis and Drought Indices Comparison
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    Chapter 9 Conjunction Model Design for Intermittent Streamflow Forecasts: Extreme Learning Machine with Discrete Wavelet Transform
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    Chapter 10 Systematic Integration of Artificial Intelligence Toward Evaluating Response of Materials and Structures in Extreme Conditions
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    Chapter 11 Machine Learning to Derive Unified Material Models for Steel Under Fire Conditions
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    Chapter 12 Energy Dissipation in Rough Chute: Experimental Approach Versus Artificial Intelligence Modeling
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    Chapter 13 Morphological Changes of Floodplain Reach of Jhelum River, India, from 1984 to 2018
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    Chapter 14 Spatial Modeling of Soil Erosion Susceptibility with Support Vector Machine
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    Chapter 15 Spatial Prediction of Landslide Susceptibility Using Random Forest Algorithm
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    Chapter 16 Artificial Neural Networks for Prediction of Steadman Heat Index
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    Chapter 17 Daily Flood Forecasts with Intelligent Data Analytic Models: Multivariate Empirical Mode Decomposition-Based Modeling Methods
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    Chapter 18 Machine Learning Method in Prediction Streamflow Considering Periodicity Component
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    Chapter 19 Empirical Model for the Assessment of Climate Change Impacts on Spatial Pattern of Water Availability in Nigeria
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    Chapter 20 Prediction of River Water Quality Parameters Using Soft Computing Techniques
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    Chapter 21 Soft Computing Applications in Air Pollution Meteorology
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Title
Intelligent Data Analytics for Decision-Support Systems in Hazard Mitigation
Published by
Springer Singapore, October 2020
DOI 10.1007/978-981-15-5772-9
ISBNs
978-9-81-155771-2, 978-9-81-155772-9
Editors

Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur, Yaseen, Zaher Mundher

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