Wavelet-linear genetic programming: A new approach for modeling monthly streamflow

M Ravansalar, T Rajaee, O Kisi - Journal of Hydrology, 2017 - Elsevier
The streamflows are important and effective factors in stream ecosystems and its accurate
prediction is an essential and important issue in water resources and environmental …

Machine learning approaches for adequate prediction of flow resistance in alluvial channels with bedforms

AA Mir, M Patel - Water Science & Technology, 2024 - iwaponline.com
In natural rivers, flow conditions are mainly dependent on flow resistance and type of
roughness. The interactions among flow and bedforms are complex in nature as bedform …

Evaluation of ultimate conditions of FRP-confined concrete columns using genetic programming

JC Lim, M Karakus, T Ozbakkaloglu - Computers & Structures, 2016 - Elsevier
A large database consisting of 832 axial compression tests results of fiber reinforced
polymer (FRP)-confined concrete specimens was assembled. Using the test database …

Modeling the infiltration process with soft computing techniques

P Sihag, B Singh, A Sepah Vand… - ISH Journal of Hydraulic …, 2020 - Taylor & Francis
Abstract Knowledge of infiltration process is very helpful in designing and planning of
irrigation networks. In this study, the Artificial Neural Network (ANN) technique was used to …

Comparative study on the machine learning and regression-based approaches to predict the hydraulic jump sequent depth ratio

S Baharvand, A Jozaghi, R Fatahi-Alkouhi… - Iranian Journal of …, 2021 - Springer
The hydraulic jump phenomenon plays a significant role in dissipating the energy of the
upstream current in either natural or artificial waterways. River's bed roughness is defined as …

Evaluation of GA-SVR method for modeling bed load transport in gravel-bed rivers

K Roushangar, A Koosheh - Journal of Hydrology, 2015 - Elsevier
The aim of the present study is to apply Support Vector Regression (SVR) method to predict
bed load transport rates for three gravel-bed rivers. Different combinations of hydraulic …

[HTML][HTML] Develo** a model based on the radial basis function to predict the compressive strength of concrete containing fly ash

AM Mayet, AA Al-Qahtani, RMA Qaisi, I Ahmad… - Buildings, 2022 - mdpi.com
A supplemental pozzolanic material such as fly ash may result in a reduction in the
concrete's adverse environmental effect by reducing the discharge of carbon dioxide …

Develo** extended and unscented kalman filter-based neural networks to predict cluster-induced roughness in gravel bed rivers

M Karbasi, M Ghasemian, M Jamei, A Malik… - Water Resources …, 2024 - Springer
Flow resistance in natural gravel-bed rivers must be precisely predicted in order for water-
related infrastructure to be designed effectively. Cluster microforms are significant factors in …

Evaluation of a two-stage SVM and spatial statistics methods for modeling monthly river suspended sediment load

V Nourani, F Alizadeh, K Roushangar - Water Resources Management, 2016 - Springer
This study is aimed on successful modeling of Ajichay River Suspended Sediment Load
(SSL) which is significant object in watershed planning and management. Therefore, a two …

Revisiting the estimation of Colebrook friction factor: a comparison between artificial intelligence models and CW based explicit equations

M Niazkar - KSCE Journal of Civil Engineering, 2019 - Springer
Abstract Application of Colebrook-White (CW) relation for calculating Darcy-Weisbach (DW)
friction factor has been widely accepted in literature. However, its implicit formation made it …