Journal of Computer and Communications

Journal of Computer and Communications

ISSN Print: 2327-5219
ISSN Online: 2327-5227
www.scirp.org/journal/jcc
E-mail: jcc@scirp.org
"Neural Network Modeling and Prediction of Surface Roughness in Machining Aluminum Alloys"
written by N. Fang, N. Fang, P. Srinivasa Pai, N. Edwards,
published by Journal of Computer and Communications, Vol.4 No.5, 2016
has been cited by the following article(s):
  • Google Scholar
  • CrossRef
[1] Machine Learning and Artificial Intelligence in CNC Machine Tools, A Review
Sustainable Manufacturing and Service …, 2023
[2] Machine Learning-Based Modeling and Optimization in Hard Turning of Aisi d6 Steel with Advanced AlTiSiN-COATED Carbide Inserts to Predict Surface Roughness …
Surface Review and …, 2022
[3] Soft computing techniques for modelling and multi-objective optimization of magnetic field assisted powder mixed EDM process
Neural Computing and Applications, 2022
[4] Machine learning based modelling and optimization in hard turning of AISI D6 steel with newly developed AlTiSiN coated carbide tool
arXiv preprint arXiv …, 2022
[5] Neural-Network-Based Approaches for Optimization of Machining Parameters Using Small Dataset
Materials, 2022
[6] Artificial intelligence-based surface roughness estimation modelling for milling of AA6061 alloy
2021
[7] Optimal cutting state predictions in internal turning operation with nano-SiC/GFRE composite layered boring tools
2021
[8] An improved algorithm to predict the mechanical properties of nuclear grade 316 stainless steel under elevated-temperature liquid sodium
2021
[9] Data‐driven framework for the prediction of cutting force in turning
IET Collaborative Intelligent …, 2020
[10] Data-driven framework for the prediction of cutting force in turning
2020
[11] Application of Fuzzy Logic in the Analysis of Surface Roughness of Thin-Walled Aluminum Parts
2019
[12] A Review of Artificial Intelligence Technologies to Achieve Machining Objectives
Cognitive Social Mining Applications in Data Analytics and Forensics, 2019
[13] A Comparative Study between Regression and Neural Networks for Modeling Al6082-T6 Alloy Drilling
2019
[14] Research on Establishing Prediction Model for Aerospace Aluminum Alloy Milling Force with the Help of RBF Neural Network
2018
[15] Optimization of Cutting Parameters in Cs in CNC Turning of AISI 304 & AISI 316 Stainless Steel
International journal of Trend in Scientific Research and Development, 2018
[16] MONITORING OF BIOSURFACTANT PRODUCTION BY Bacillus subtilis USING BEET PEEL AS CULTURE MEDIUM VIA THE DEVELOPMENT OF A …
2018
[17] Dynamic Bayesian Network-based Approach by Integrating Sensor Deployment for Machining Process Monitoring
2018
[18] Modeling for Prediction of Surface Roughness and Experimental Research in Ultra-Precision Flycutting Machining
2018
[19] Study on Parameter Optimization of Cutting Surface Roughness of Aluminum Alloy
2018
[20] Monitoring of biosurfactant production by Bacillus subtilis using beet peel as culture medium via the development of a neural soft-sensor in an electronic …
2018
[21] Monitoring of biosurfactant production by Bacillus subtilis using beet peel as culture medium via the development of a neural soft-sensor in an electronic spreadsheet
2018
[22] Küreselleştirme isil İşlemi uygulanmiş AISI 1050 Çeliğinin yüzey pürüzlülük değerlerinin yapay sinir ağlari ile modellenmesi
2017
[23] Machine Learning and Artificial Intelligence in CNC Machine Tools, A
Free SCIRP Newsletters
Copyright © 2006-2024 Scientific Research Publishing Inc. All Rights Reserved.
Top