Solar radiation prediction using different techniques: model evaluation and comparison

L Wang, O Kisi, M Zounemat-Kermani… - … and Sustainable Energy …, 2016 - Elsevier
Daily observations of meteorological parameters, air temperature, air pressure, relative
humidity, water vapor pressure and sunshine duration hours observed at 12 stations in …

[HTML][HTML] Groundwater quality forecasting modelling using artificial intelligence: A review

NFC Nordin, NS Mohd, S Koting, Z Ismail… - Groundwater for …, 2021 - Elsevier
This review paper closely explores the techniques and significances of the most potent
artificial intelligence (AI) approaches in a concise and integrated way, specifically in the …

Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS

MK Goyal, B Bharti, J Quilty, J Adamowski… - Expert systems with …, 2014 - Elsevier
This paper investigates the abilities of Artificial Neural Networks (ANN), Least Squares–
Support Vector Regression (LS-SVR), Fuzzy Logic, and Adaptive Neuro-Fuzzy Inference …

A comparison of various artificial intelligence approaches performance for estimating suspended sediment load of river systems: a case study in United States

E Olyaie, H Banejad, KW Chau, AM Melesse - … monitoring and assessment, 2015 - Springer
Accurate and reliable suspended sediment load (SSL) prediction models are necessary for
planning and management of water resource structures. More recently, soft computing …

Daily suspended sediment load prediction using artificial neural networks and support vector machines

EK Lafdani, AM Nia, A Ahmadi - Journal of Hydrology, 2013 - Elsevier
In recent decades, development of artificial intelligence, as a predictor for hydrological
phenomenon, has created a great change in predictions. This paper investigates the …

A whale optimization algorithm-trained artificial neural network for smart grid cyber intrusion detection

L Haghnegahdar, Y Wang - Neural computing and applications, 2020 - Springer
The smart grid is a revolutionary, intelligent, next-generation power system. Due to its cyber
infrastructure nature, it must be able to accurately and detect potential cyber-attacks and …

ANN based sediment prediction model utilizing different input scenarios

HA Afan, A El-Shafie, ZM Yaseen, MM Hameed… - Water resources …, 2015 - Springer
Modeling sediment load is a significant factor in water resources engineering as it affects
directly the design and management of water resources. In this study, artificial neural …

Suspended sediment estimation using neuro-fuzzy and neural network approaches/Estimation des matières en suspension par des approches neurofloues et à base …

O Kisi - Hydrological sciences journal, 2005 - Taylor & Francis
The abilities of neuro-fuzzy (NF) and neural network (NN) approaches to model the
streamflow–suspended sediment relationship are investigated. The NF and NN models are …

[HTML][HTML] A comparison of performance of SWAT and machine learning models for predicting sediment load in a forested Basin, Northern Spain

P Jimeno-Sáez, R Martinez-Espana, J Casalí… - Catena, 2022 - Elsevier
In water bodies, sediment transport is a potential source of numerous negative effects on
water resource projects and can damage environmental services. Two machine learning …

A hybrid double feedforward neural network for suspended sediment load estimation

XY Chen, KW Chau - Water resources management, 2016 - Springer
Estimation of suspended sediment loads (SSL) in rivers is an important issue in water
resources management and planning. This study proposes a hybrid double feedforward …