Volume 2, Issue 6 - 1 Article
This issue presents a research paper about predicting when machine parts called bearings will wear out. The study uses a special computer method called Neural Network Regression (NNR) and tests it using Microsoft’s Azure cloud service. The researchers found that NNR works better than other methods for figuring out how long bearings will last. This is important because it can help factories keep their machines running smoothly without unexpected breakdowns. The study used real data from NASA and showed that this method is easy to use, even without complex programming skills.
Front Cover
Journal of Engineering Research and Sciences, Volume 2, Issue 6, Page # i–i, 2023
Editorial Board
Journal of Engineering Research and Sciences, Volume 2, Issue 6, Page # ii–ii, 2023
Editorial
by Paul Andrew
Journal of Engineering Research and Sciences, Volume 2, Issue 6, Page # iii–iii, 2023
Table of Contents
Journal of Engineering Research and Sciences, Volume 2, Issue 6, Page # iv–iv, 2023
NNR Artificial Intelligence Model in Azure for Bearing Prediction and Analysis
by Henry Ogbemudia Omoregbee, Mabel Usunobun Olanipekun and Bright Aghogho Edward
Journal of Engineering Research and Sciences, Volume 2, Issue 6, Page # 1-9, 2023; DOI: 10.55708/js0206001
Abstract: Neural Network regression (NNR) is considered more effective as compared to multiple neural networks model readily available in Azure to evaluate the Remaining Useful Life (RUL) of bearing in this work because it performs better than other models when used and was demonstrated as a non-programing technique for analyzing enormous data without the use of… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2023 and the Section Artificial Intelligence – Computer Science (AIC))