Application of machine learning, deep learning and optimization algorithms in geoengineering and geoscience: Comprehensive review and future challenge

W Zhang, X Gu, L Tang, Y Yin, D Liu, Y Zhang - Gondwana Research, 2022 - Elsevier
Abstract The so-called Fourth Paradigm has witnessed a boom during the past two decades,
with large volumes of observational data becoming available to scientists and engineers …

A review of the recent development in machining parameter optimization

M Soori, M Asmael - Jordan Journal of Mechanical and Industrial …, 2022 - hal.science
The optimization process is applied to the machining operations in order to provide
continual improvement in accuracy and quality of produced parts. The effects of machining …

Waterjet machining and research developments: A review

X Liu, Z Liang, G Wen, X Yuan - The International Journal of Advanced …, 2019 - Springer
Waterjet machining has attracted great attention in the conditions of hard-to-machine
materials, microstructures, or complicated industrial components, and it has become well …

Dynamic parameters identification for sliding joints of surface grinder based on deep neural network modeling

W Zhang, X Liu, Z Huang, J Zhu - Advances in Mechanical …, 2021 - journals.sagepub.com
Dynamic parameters of joints are indispensable factors affecting performance of machine
tools. In order to obtain the stiffness and damping of sliding joints between the working …

Parameter optimization of advanced machining processes using cuckoo optimization algorithm and hoopoe heuristic

MA Mellal, EJ Williams - Journal of Intelligent Manufacturing, 2016 - Springer
Unconventional machining processes (communally named advanced or modern machining
processes) are widely used by manufacturing industries. These advanced machining …

Prediction and optimization of process parameters of green composites in AWJM process using response surface methodology

Jagadish, S Bhowmik, A Ray - The International Journal of Advanced …, 2016 - Springer
The objective of this paper is to develop a response surface methodology (RSM)-based
optimization design for process parameter optimization of abrasive water jet machining …

Multi-objective optimization of machining and micro-machining processes using non-dominated sorting teaching–learning-based optimization algorithm

RV Rao, DP Rai, J Balic - Journal of Intelligent Manufacturing, 2018 - Springer
Selection of optimum machining parameters is vital to the machining processes in order to
ensure the quality of the product, reduce the machining cost, increasing the productivity and …

Prediction of surface roughness and depth of cut in abrasive waterjet milling of alumina ceramic using Machine learning algorithms

R Prabhu, M Kanthababu - Expert Systems with Applications, 2024 - Elsevier
In abrasive waterjet (AWJ) milling process, the ability to accurately predict outcomes such as
surface roughness (R a) and depth of cut (DoC) holds immense significance for cost …

Multi-objective optimization of abrasive waterjet machining process using Jaya algorithm and PROMETHEE Method

RV Rao, DP Rai, J Balic - Journal of Intelligent Manufacturing, 2019 - Springer
In this work, the process parameters optimization problems of abrasive waterjet machining
process are solved using a recently proposed metaheuristic optimization algorithm named …

A hybrid GA-ANFIS and F-Race tuned harmony search algorithm for Multi-Response optimization of Non-Traditional Machining process

R Devaraj, SK Mahalingam, B Esakki, A Astarita… - Expert Systems with …, 2022 - Elsevier
The present study focuses on development of prediction models with respect to various cut
quality characteristics such as material removal rate, kerf taper and surface roughness for a …