A review of machine learning methods for drought hazard monitoring and forecasting: Current research trends, challenges, and future research directions

Author:

Prodhan Foyez AhmedORCID,Zhang Jiahua,Hasan Shaikh Shamim,Pangali Sharma Til Prasad,Mohana Hasiba Pervin

Publisher

Elsevier BV

Subject

Ecological Modeling,Environmental Engineering,Software

Reference100 articles.

1. March). A Deep Learning Based Approach for Long-Term Drought Prediction;Agana,2017

2. Multi-stage committee based extreme learning machine model incorporating the influence of climate parameters and seasonality on drought forecasting;Ali;Comput. Electron. Agric.,2018

3. Selection of appropriate time scale with Boruta algorithm for regional drought monitoring using multi-scaler drought index;Ali;Tellus Dyn. Meteorol. Oceanogr.,2019

4. A fusion-based methodology for meteorological drought estimation using remote sensing data;Alizadeh;Rem. Sens. Environ.,2018

5. Regional hydrological drought monitoring using principal components analysis;Arabzadeh;J. Irrigat. Drain. Eng.,2015

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