Artificial intelligence application in drought assessment, monitoring and forecasting: a review

A Kikon, PC Deka - Stochastic Environmental Research and Risk …, 2022 - Springer
Drought is a natural hazard creating havoc on economic, social and environmental aspects.
As a result of its slow and creeping nature, it is problematic to establish the onset as well as …

Support vector regression optimized by meta-heuristic algorithms for daily streamflow prediction

A Malik, Y Tikhamarine, D Souag-Gamane… - … Research and Risk …, 2020 - Springer
Accurate and reliable prediction of streamflow is vital to the optimization of water resources
management, reservoir flood operations, catchment, and urban water management. In this …

Prediction of meteorological drought by using hybrid support vector regression optimized with HHO versus PSO algorithms

A Malik, Y Tikhamarine, SS Sammen, SI Abba… - … Science and Pollution …, 2021 - Springer
Drought is considered one of the costliest natural disasters that result in water scarcity and
crop damage almost every year. Drought monitoring and forecasting are essential for the …

Groundwater quality evaluation using hybrid model of the multi-layer perceptron combined with neural-evolutionary regression techniques: case study of Shiraz plain

H Moayedi, M Salari, AA Dehrashid, BN Le - … Environmental Research and …, 2023 - Springer
In recent decades, qualitative and quantitative assessments of groundwater sources reveal
that efficient and accurate optimization approaches may assist in solving the multiple …

Forecasting standardized precipitation index using data intelligence models: regional investigation of Bangladesh

ZM Yaseen, M Ali, A Sharafati, N Al-Ansari, S Shahid - Scientific reports, 2021 - nature.com
A noticeable increase in drought frequency and severity has been observed across the
globe due to climate change, which attracted scientists in development of drought prediction …

Development of a TVF-EMD-based multi-decomposition technique integrated with Encoder-Decoder-Bidirectional-LSTM for monthly rainfall forecasting

M Jamei, M Ali, A Malik, M Karbasi, P Rai… - Journal of Hydrology, 2023 - Elsevier
Accurate forecasting of rainfall is extremely important due to its complex nature and
enormous impacts on hydrology, floods, droughts, agriculture, and monitoring of pollutant …

Artificial neural network optimized with a genetic algorithm for seasonal groundwater table depth prediction in Uttar Pradesh, India

K Pandey, S Kumar, A Malik, A Kuriqi - Sustainability, 2020 - mdpi.com
Accurate information about groundwater level prediction is crucial for effective planning and
management of groundwater resources. In the present study, the Artificial Neural Network …

Simulation of seepage flow through embankment dam by using a novel extended Kalman filter based neural network paradigm: Case study of Fontaine Gazelles Dam …

I Rehamnia, B Benlaoukli, M Jamei, M Karbasi, A Malik - Measurement, 2021 - Elsevier
Seepage flow through embankment dam is one of the most influential factors in failures of
them. Thus, the monitoring and accurate measuring of seepage are crucial for the safety and …

Development of wavelet-based kalman online sequential extreme learning machine optimized with boruta-random forest for drought index forecasting

M Jamei, I Ahmadianfar, M Karbasi, A Malik… - … Applications of Artificial …, 2023 - Elsevier
Drought is a stochastic and recurring hydrological natural hazard that occurs due to a
shortage of precipitation over a period of time. Drought forecasting in water resources …

[HTML][HTML] Multi-steps drought forecasting in arid and humid climate environments: Development of integrative machine learning model

M Karbasi, M Jamei, A Malik, O Kisi… - Agricultural Water …, 2023 - Elsevier
In the current study, the Standardized Precipitation Evaporation Index (SPEI) was forecasted
using a combination of the empirical wavelet transform (EWT), discrete wavelet transforms …