Data-driven models for predicting solar radiation in semi-arid regions

M Jamei, N Bailek, K Bouchouicha… - Computers, Materials …, 2023 - diva-portal.org
Solar energy represents one of the most important renewable energy sources contributing to
the energy transition process. Considering that the observation of daily global solar radiation …

A review of hybrid soft computing and data pre-processing techniques to forecast freshwater quality's parameters: Current trends and future directions

ZS Khudhair, SL Zubaidi, S Ortega-Martorell… - Environments, 2022 - mdpi.com
Water quality has a significant influence on human health. As a result, water quality
parameter modelling is one of the most challenging problems in the water sector. Therefore …

An improved adaptive neuro fuzzy inference system model using conjoined metaheuristic algorithms for electrical conductivity prediction

I Ahmadianfar, S Shirvani-Hosseini, J He… - Scientific Reports, 2022 - nature.com
Precise prediction of water quality parameters plays a significant role in making an early
alert of water pollution and making better decisions for the management of water resources …

Application of stacking hybrid machine learning algorithms in delineating multi-type flooding in Bangladesh

M Rahman, N Chen, A Elbeltagi, MM Islam… - Journal of …, 2021 - Elsevier
Floods are among the most devastating natural hazards in Bangladesh. The country
experiences multi-type floods (ie, fluvial, flash, pluvial, and surge floods) every year …

A novel multiple-kernel support vector regression algorithm for estimation of water quality parameters

M Najafzadeh, S Niazmardi - Natural Resources Research, 2021 - Springer
The quality of surface waters plays a key role in the sustainability of ecological systems.
Measuring water quality parameters (WQPs) is of high importance in the management of …

A systematic review on machine learning algorithms used for forecasting lake‐water level fluctuations

SR Sannasi Chakravarthy… - Concurrency and …, 2022 - Wiley Online Library
Globally, the water‐level fluctuations in lakes are a dynamic and complex process. The
fluctuation is characterized by higher non‐linearity and stochasticity, making it quite hard to …

Prediction of surface water total dissolved solids using hybridized wavelet-multigene genetic programming: New approach

M Jamei, I Ahmadianfar, X Chu, ZM Yaseen - Journal of Hydrology, 2020 - Elsevier
Total dissolved solids (TDS) are recognized as an essential indicator of surface water
quality. The current research investigates the potential of a novel computer aid approach …

Groundwater level modeling framework by combining the wavelet transform with a long short-term memory data-driven model

C Wu, X Zhang, W Wang, C Lu, Y Zhang, W Qin… - Science of The Total …, 2021 - Elsevier
Developing models that can accurately simulate groundwater level is important for water
resource management and aquifer protection. In particular, machine learning tools provide a …

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 …

Multi-step daily forecasting of reference evapotranspiration for different climates of India: A modern multivariate complementary technique reinforced with ridge …

A Malik, M Jamei, M Ali, R Prasad, M Karbasi… - Agricultural Water …, 2022 - Elsevier
Accurate ahead forecasting of reference evapotranspiration (ET o) is crucial for effective
irrigation scheduling and management of water resources on a regional scale. A variety of …