Application of artificial intelligence in geotechnical engineering: A state-of-the-art review

A Baghbani, T Choudhury, S Costa, J Reiner - Earth-Science Reviews, 2022 - Elsevier
Geotechnical engineering deals with soils and rocks and their use in engineering
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …

Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review

F Fahimi, ZM Yaseen, A El-shafie - Theoretical and applied climatology, 2017 - Springer
Since the middle of the twentieth century, artificial intelligence (AI) models have been used
widely in engineering and science problems. Water resource variable modeling and …

Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm

Y Tikhamarine, D Souag-Gamane, AN Ahmed, O Kisi… - Journal of …, 2020 - Elsevier
Monthly streamflow forecasting is required for short-and long-term water resources
management especially in extreme events such as flood and drought. Therefore, there is …

Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq

ZM Yaseen, O Jaafar, RC Deo, O Kisi, J Adamowski… - Journal of …, 2016 - Elsevier
Monthly stream-flow forecasting can yield important information for hydrological applications
including sustainable design of rural and urban water management systems, optimization of …

Selecting the best model to estimate potential evapotranspiration with respect to climate change and magnitudes of extreme events

M Valipour, MAG Sefidkouhi, M Raeini - Agricultural Water Management, 2017 - Elsevier
There are a lot of investigations to select the best model to estimate potential
evapotranspiration (ET o) in a certain climate or region. In this paper, the types of climate …

Application of artificial intelligence (AI) techniques in water quality index prediction: a case study in tropical region, Malaysia

M Hameed, SS Sharqi, ZM Yaseen, HA Afan… - Neural Computing and …, 2017 - Springer
The management of river water quality is one the most significant environmental challenges.
Water quality index (WQI) describes several water quality variables at a certain aquatic …

Rainfall-runoff modelling using improved machine learning methods: Harris hawks optimizer vs. particle swarm optimization

Y Tikhamarine, D Souag-Gamane, AN Ahmed… - Journal of …, 2020 - Elsevier
Rainfall and runoff are considered the main components in the hydrological cycle.
Developing an accurate model to capture the dynamic connection between rainfall and …

[PDF][PDF] Comparison of artificial neural network transfer functions abilities to simulate extreme runoff data

M Dorofki, AH Elshafie, O Jaafar… - International …, 2012 - researchgate.net
Approximately most of rainfall-runoff models have a good performance, especially where
rainfall and obtained runoff data are near to average in standard normal distribution. While …

Input attributes optimization using the feasibility of genetic nature inspired algorithm: application of river flow forecasting

HA Afan, MF Allawi, A El-Shafie, ZM Yaseen… - Scientific Reports, 2020 - nature.com
In nature, streamflow pattern is characterized with high non-linearity and non-stationarity.
Developing an accurate forecasting model for a streamflow is highly essential for several …

RBFNN versus FFNN for daily river flow forecasting at Johor River, Malaysia

ZM Yaseen, A El-Shafie, HA Afan, M Hameed… - Neural Computing and …, 2016 - Springer
Streamflow forecasting can have a significant economic impact, as this can help in water
resources management and in providing protection from water scarcities and possible flood …