Applications of hybrid wavelet–artificial intelligence models in hydrology: a review
Accurate and reliable water resources planning and management to ensure sustainable use
of watershed resources cannot be achieved without precise and reliable models …
of watershed resources cannot be achieved without precise and reliable models …
Deep learning in hydrology and water resources disciplines: Concepts, methods, applications, and research directions
KP Tripathy, AK Mishra - Journal of Hydrology, 2023 - Elsevier
Deep Learning (DL) methods have gained significant recognition in hydrology and water
resources applications in recent years. Beginning with a discussion on fundamental …
resources applications in recent years. Beginning with a discussion on fundamental …
Prediction of sodium hazard of irrigation purpose using artificial neural network modelling
VK Gautam, CB Pande, KN Moharir, AM Varade… - Sustainability, 2023 - mdpi.com
The present study was carried out using artificial neural network (ANN) model for predicting
the sodium hazardness, ie, sodium adsorption ratio (SAR), percent sodium (% Na) residual …
the sodium hazardness, ie, sodium adsorption ratio (SAR), percent sodium (% Na) residual …
Development of neuro-fuzzy and neuro-bee predictive models for prediction of the safety factor of eco-protection slopes
This study is aimed to investigate the surface eco-protection techniques for cohesive soil
slopes along the selected Guthrie Corridor Expressway (GCE) stretch by way of analyzing a …
slopes along the selected Guthrie Corridor Expressway (GCE) stretch by way of analyzing a …
Projection of temperature and precipitation in the Mediterranean region through multi-model ensemble from CMIP6
In this study, future projections of monthly total precipitation and monthly average
temperatures are carried out using 22 global circulation models (GCMs) from phase 6 of the …
temperatures are carried out using 22 global circulation models (GCMs) from phase 6 of the …
Spatial-temporal flood inundation nowcasts by fusing machine learning methods and principal component analysis
The frequency and severity of floods have noticeably increased worldwide in the last
decades due to climate change and urbanization. This study aims to build an urban flood …
decades due to climate change and urbanization. This study aims to build an urban flood …
Improving forecasting accuracy of medium and long-term runoff using artificial neural network based on EEMD decomposition
Hydrological time series forecasting is one of the most important applications in modern
hydrology, especially for the effective reservoir management. In this research, an artificial …
hydrology, especially for the effective reservoir management. In this research, an artificial …
An emotional ANN (EANN) approach to modeling rainfall-runoff process
V Nourani - Journal of Hydrology, 2017 - Elsevier
This paper presents the first hydrological implementation of Emotional Artificial Neural
Network (EANN), as a new generation of Artificial Intelligence-based models for daily rainfall …
Network (EANN), as a new generation of Artificial Intelligence-based models for daily rainfall …
Application of wavelet-artificial intelligence hybrid models for water quality prediction: a case study in Aji-Chay River, Iran
Abstract The accuracy of Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference
System (ANFIS), wavelet-ANN and wavelet-ANFIS in predicting monthly water salinity levels …
System (ANFIS), wavelet-ANN and wavelet-ANFIS in predicting monthly water salinity levels …
Forecasting of TBM advance rate in hard rock condition based on artificial neural network and genetic programming techniques
J Zhou, B Yazdani Bejarbaneh… - Bulletin of Engineering …, 2020 - Springer
The efficiency of tunnel boring machine (TBM) is regarded as a key factor in successfully
undertaking any mechanical tunneling project. In fact, an accurate forecasting of TBM …
undertaking any mechanical tunneling project. In fact, an accurate forecasting of TBM …