[HTML][HTML] A review of optimization and measurement techniques of the friction stir welding (FSW) process

DAP Prabhakar, A Korgal, AK Shettigar… - … of Manufacturing and …, 2023 - mdpi.com
This review reports on the influencing parameters on the joining parts quality of tools and
techniques applied for conducting process analysis and optimizing the friction stir welding …

A survey on projection neural networks and their applications

L Jin, S Li, B Hu, M Liu - Applied Soft Computing, 2019 - Elsevier
Constrained optimization problems arise in numerous scientific and engineering
applications, and many papers on the online solution of constrained optimization problems …

Optimization of Darcy-Forchheimer squeezing flow in nonlinear stratified fluid under convective conditions with artificial neural network

A Shafiq, AB Çolak, TN Sindhu… - Heat Transfer …, 2022 - dl.begellhouse.com
In cases when high velocity occurs, non-Darcy phenomena are essential for explaining fluid
motion in porous media and have wide range of applications. The present study displays the …

[HTML][HTML] Noise prediction of axial piston pump based on different valve materials using a modified artificial neural network model

HA Babikir, M Abd Elaziz, AH Elsheikh… - Alexandria Engineering …, 2019 - Elsevier
In this paper, an alternative method to predict the noise of a submersible Axial Piston Pump
(APP) for different valve seat materials is presented. The proposed method is composed of …

A systematic comparison of machine learning methods for modeling of dynamic processes applied to combustion emission rate modeling

JF Tuttle, LD Blackburn, K Andersson, KM Powell - Applied Energy, 2021 - Elsevier
Ten established, data-driven dynamic algorithms are surveyed and a practical guide for
understanding these methods generated. Existing Python programming packages for …

Non-parameterized ship maneuvering model of Deep Neural Networks based on real voyage data-driven

Z Wang, J Kim, N Im - Ocean Engineering, 2023 - Elsevier
Abstract While Deep Neural Network (DNN) models for ship maneuvering model are
commonly constructed using experimental model ships or simulation data, this study focuses …

Improved prediction of oscillatory heat transfer coefficient for a thermoacoustic heat exchanger using modified adaptive neuro-fuzzy inference system

M Abd Elaziz, AH Elsheikh, SW Sharshir - International Journal of …, 2019 - Elsevier
Despite the increasingly rapid advances in the thermoacoustic field, heat transfer process in
thermoacoustic-based heat exchangers has not been fully understood yet. In this study, an …

Instantaneous vehicle fuel consumption estimation using smartphones and recurrent neural networks

S Kanarachos, J Mathew, ME Fitzpatrick - Expert Systems with Applications, 2019 - Elsevier
The high level of air pollution in urban areas, caused in no small extent by road transport,
requires the implementation of continuous and accurate monitoring techniques if emissions …

[HTML][HTML] Numerical treatment for the desirability of Hall current and activation energy in the enhancement of heat transfer in a nanofluidic system

M Shoaib, SU Saqib, KS Nisar, MAZ Raja… - Arabian Journal of …, 2024 - Elsevier
The growing attractiveness of Artificial Neural Networks (ANNs) derives from their
exceptional effectiveness in handling difficult and exceptionally nonlinear mathematical …

Process Optimization and Studies on Mechanical Characteristics of AA2014/Al2O3 Nanocomposites Fabricated Through Ultrasonication Assisted Stir–Squeeze …

A Gnanavelbabu, KTS Surendran, S Kumar - International Journal of …, 2021 - Springer
The present study investigates the impact of novel ultrasonic-assisted squeeze casting
parameters on the fabrication of AA2014/Al 2 O 3 nanocomposites using the Taguchi Grey …