Evaluating the Wear Characteristics of Al 5024 Alloy with Varying SiC Nano Particle Percentages and Predictive Analysis using Artificial Neural Networks-Reference-Cited by-同舟云学术

Evaluating the Wear Characteristics of Al 5024 Alloy with Varying SiC Nano Particle Percentages and Predictive Analysis using Artificial Neural Networks

Published:2023-12-07 Issue: Volume: Page:1-6
ISSN:
Container-title:2023 International Conference on Emerging Research in Computational Science (ICERCS)
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Author:

Boddepalli Eshwararao¹,Jotiram Gujar Anantkumar²,K T Thilagham³,Al Ansari Mohammed Saleh⁴,Baburao Desai Anil⁵,Bajaj K. K.⁶

Affiliation:

1. Virginia Tech,Department of ECE,Blacksburg,United States of America,24060

2. D Y Patil College of Engineering and Technology,Department of Mechanical Engineering,Kolhapur

3. Government College of Engineering,Department of Metallurgical Engineering,Salem,Tamilnadu,India,11

4. University of Bahrain,Department of Chemical Engineering,Bahrain

5. Graphic Era Hill University Dehradun,Department of Computer Science and Engineering,Uttarakhand,India

6. RNB Global University,Faculty of Basic and Applied Sciences,Bikaner,Rajasthan,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10433896/10433898/10434038.pdf?arnumber=10434038

Reference19 articles.

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4. 3D Network Conductive Polymer/Pt Composites as Elcetrocatalyst for Methanol Oxidation

5. Multi objective prediction and optimization of control parameters in the milling of aluminium hybrid metal matrix composites using ANN and Taguchi -grey relational analysis