A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique

SS Fiyadh, SM Alardhi, M Al Omar, MM Aljumaily… - Heliyon, 2023 - cell.com
Water is the most necessary and significant element for all life on earth. Unfortunately, the
quality of the water resources is constantly declining as a result of population development …

Data-driven methods for estimating the effective thermal conductivity of nanofluids: A comprehensive review

A Zendehboudi, R Saidur, IM Mahbubul… - International journal of …, 2019 - Elsevier
There is a growing body of work in the field of nanofluids and several investigations have
been conducted on their thermal conductivities. While the experimental works require …

Optimization of operational parameters using RSM, ANN, and SVM in membrane integrated with rotating biological contactor

S Waqas, NY Harun, U Arshad, AM Laziz, SLS Mun… - Chemosphere, 2024 - Elsevier
Membrane fouling is a critical bottleneck to the widespread adoption of membrane
separation processes. It diminishes the membrane permeability and results in high …

Investigation and machine learning-based prediction of parametric effects of single point incremental forming on pillow effect and wall profile of AlMn1Mg1 aluminum …

SM Najm, I Paniti - Journal of Intelligent Manufacturing, 2023 - Springer
Today the topic of incremental sheet forming (ISF) is one of the most active areas of sheet
metal forming research. ISF can be an essential alternative to conventional sheet forming for …

A new comprehensive model for relative viscosity of various nanofluids using feed-forward back-propagation MLP neural networks

HR Ansari, MJ Zarei, S Sabbaghi… - … Communications in Heat …, 2018 - Elsevier
In this study, a comprehensive model was proposed to predict the nanofluids relative
viscosity on the basis of feedforward back-propagation network by utilizing various training …

Artificial neural network for modeling and investigating the effects of forming tool characteristics on the accuracy and formability of thin aluminum alloy blanks when …

SM Najm, I Paniti - The International Journal of Advanced Manufacturing …, 2021 - Springer
Abstract Incremental Sheet Forming (ISF) has attracted attention due to its flexibility as far as
its forming process and complexity in the deformation mode are concerned. Single Point …

Parametric effects of single point incremental forming on hardness of AA1100 aluminium alloy sheets

SM Najm, I Paniti, T Trzepieciński, SA Nama… - Materials, 2021 - mdpi.com
When using a unique tool with different controlled path strategies in the absence of a punch
and die, the local plastic deformation of a sheet is called Single Point Incremental Forming …

Application of artificial neural networks to the analysis of friction behaviour in a drawbead profile in sheet metal forming

T Trzepieciński, SM Najm - Materials, 2022 - mdpi.com
Drawbeads are used when forming drawpieces with complex shapes to equalise the flow
resistance of a material around the perimeter of the drawpiece or to change the state of …

Modelling and parameter identification of coefficient of friction for deep-drawing quality steel sheets using the CatBoost machine learning algorithm and neural …

SM Najm, T Trzepieciński, M Kowalik - The International Journal of …, 2023 - Springer
The development of models for the coefficient of friction is difficult due to many factors
influencing its value and many tribological phenomena that accompany contact between …

Prediction of pool boiling heat transfer coefficient for various nano-refrigerants utilizing artificial neural networks

MJ Zarei, HR Ansari, P Keshavarz… - Journal of Thermal …, 2020 - Springer
In the present research, an artificial neural network model was developed to predict the pool
boiling heat transfer coefficient (HTC) of refrigerant-based nanofluids based on a large …