Machine Learning and Statistical Approach to Predict and Analyze Wear Rates in Copper Surface Composites

被引：0
|
作者：
Titus Thankachan
K. Soorya Prakash
V. Kavimani
S. R. Silambarasan
机构：
[1] Karpagam College of Engineering,Mechanical Engineering
[2] Anna University Regional Campus,Mechanical Engineering
[3] Karpagam Academy of Higher Education,Mechanical Engineering
来源：
Metals and Materials International | 2021年 / 27卷
关键词：
Friction stir processing; Boron nitride; Surface engineering; Wear rate;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：220 / 234
页数：14
相关论文
共 50 条
  • [1] Machine Learning and Statistical Approach to Predict and Analyze Wear Rates in Copper Surface Composites
    Thankachan, Titus
    Prakash, K. Soorya
    Kavimani, V
    Silambarasan, S. R.
    [J]. METALS AND MATERIALS INTERNATIONAL, 2021, 27 (02) : 220 - 234
  • [2] Machine Learning Approach to Analyze and Predict the Popularity of Tweets with Images
    Joseph, Nimish
    Sultan, Amir
    Kar, Arpan Kumar
    Ilavarasan, P. Vigneswara
    [J]. CHALLENGES AND OPPORTUNITIES IN THE DIGITAL ERA, 2018, 11195 : 567 - 576
  • [3] A machine learning approach to predict the wear behaviour of steels
    Rajput, Ajeet Singh
    Das, Sourav
    [J]. TRIBOLOGY INTERNATIONAL, 2023, 185
  • [4] Proposing a Machine Learning Approach to Analyze and Predict Employment and its Factors
    Garcia-Penalvo, Francisco J.
    Cruz-Benito, Juan
    Martin-Gonzalez, Martin
    Vazquez-Ingelmo, Andrea
    Carlos Sanchez-Prieto, Jose
    Theron, Roberto
    [J]. INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE, 2018, 5 (02): : 39 - 45
  • [5] Optimizing the Tribological Behavior of Hybrid Copper Surface Composites Using Statistical and Machine Learning Techniques
    Thankachan, Titus
    Prakash, K. Soorya
    Kamarthin, Mujiburrahman
    [J]. JOURNAL OF TRIBOLOGY-TRANSACTIONS OF THE ASME, 2018, 140 (03):
  • [6] Machine Learning Approach to Analyze the Surface Properties of Biological Materials
    Rickert, Carolin A.
    Hayta, Elif N.
    Selle, Daniel M.
    Kouroudis, Ioannis
    Harth, Milan
    Gagliardi, Alessio
    Lieleg, Oliver
    [J]. ACS BIOMATERIALS SCIENCE & ENGINEERING, 2021, 7 (09): : 4614 - 4625
  • [7] Use of Machine Learning to Analyze and - Hopefully - Predict Volcano Activity
    Parra, Justin
    Fuentes, Olac
    Anthony, Elizabeth
    Kreinovich, Vladik
    [J]. ACTA POLYTECHNICA HUNGARICA, 2017, 14 (03) : 209 - 221
  • [8] Using machine learning to analyze and predict construction task productivity
    Florez-Perez, Laura
    Song, Zhiyuan
    Cortissoz, Jean C.
    [J]. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 2022, 37 (12) : 1602 - 1616
  • [9] Machine Learning: A Practical Approach on the Statistical Learning
    Liu, Shin Ta
    [J]. TECHNOMETRICS, 2020, 62 (04) : 560 - 561
  • [10] A STATISTICAL MACHINE LEARNING APPROACH TO PREDICT RESIDENTIAL HVAC USAGE WITH LAGGED ENVIRONMENTAL PREDICTORS
    Baath, Jashanjeet
    Little, Madelyn
    Bhattacharya, Anirban
    Bandyopadhyay, Arkasama
    [J]. PROCEEDINGS OF ASME 2023 INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, IMECE2023, VOL 7, 2023,
12345