Modeling stage–discharge–sediment using support vector machine and artificial neural network coupled with wavelet transform
Many real water issues involve rivers' sediment load or the load that rivers can bring without
degrading the fluvial ecosystem. Therefore, the assessment of sediments carried by a river is …
degrading the fluvial ecosystem. Therefore, the assessment of sediments carried by a river is …
Development and evaluation of the cascade correlation neural network and the random forest models for river stage and river flow prediction in Australia
Accurately predicting river flows over daily timescales is considered as an important task for
sustainable management of freshwater ecosystems, agricultural applications, and water …
sustainable management of freshwater ecosystems, agricultural applications, and water …
River flow prediction using hybrid PSOGSA algorithm based on feed-forward neural network
River flow modeling plays an important role in water resources management. This research
aims at develo** a hybrid model that integrates the feed-forward neural network (FNN) …
aims at develo** a hybrid model that integrates the feed-forward neural network (FNN) …
Modeling river discharge time series using support vector machine and artificial neural networks
Discharge time series were investigated using predictive models of support vector machine
(SVM) and artificial neural network (ANN) and their performances were compared with two …
(SVM) and artificial neural network (ANN) and their performances were compared with two …
Comparison of improved relevance vector machines for streamflow predictions
RM Adnan, RR Mostafa, HL Dai… - Journal of …, 2024 - Wiley Online Library
This study investigates the feasibility of relevance vector machine tuned with dwarf
mongoose optimization algorithm in modeling monthly streamflow. The proposed method is …
mongoose optimization algorithm in modeling monthly streamflow. The proposed method is …
[HTML][HTML] Estimation of instantaneous peak flow using machine-learning models and empirical formula in peninsular Spain
The design of hydraulic structures and flood risk management is often based on
instantaneous peak flow (IPF). However, available flow time series with high temporal …
instantaneous peak flow (IPF). However, available flow time series with high temporal …
Modelling stage–discharge relationship of Himalayan river using ANN, SVM and ANFIS
Modelling the stage–discharge relationship is vital for precise discharge estimation, which is
essential in reservoir operation, design of hydraulic structures, flood and drought control …
essential in reservoir operation, design of hydraulic structures, flood and drought control …
A novel hybrid neural network based on phase space reconstruction technique for daily river flow prediction
H Delafrouz, A Ghaheri, MA Ghorbani - Soft Computing, 2018 - Springer
The main purpose of this study is to construct a new hybrid model (PSR–ANN) by combining
phase space reconstruction (PSR) and artificial neural network (ANN) techniques to raise …
phase space reconstruction (PSR) and artificial neural network (ANN) techniques to raise …
A comparative study of wavelet and empirical mode decomposition-based GPR models for river discharge relationship modeling at consecutive hydrometric stations
The river stage–discharge relationship has an important impact on modeling, planning, and
management of river basins and water resources. In this study, the capability of the …
management of river basins and water resources. In this study, the capability of the …
Stage-discharge prediction in natural rivers using an innovative approach
MF Maghrebi, A Ahmadi - Journal of hydrology, 2017 - Elsevier
Determination of stage-discharge relationships in natural rivers is extremely important in
flood control projects. Observational data at various stages cannot be collected …
flood control projects. Observational data at various stages cannot be collected …