Lumen Maintenance And Trend Predictions For Light-Emitting Diodes Using Regression Analysis

This study aims to improve the prediction of lumen maintenance life under different thermal-electrical conditions and the Eyring model is proposed in this study. The model parameters are determined by regression approach, which provides the goodness of fit of the prediction model as well as the pr...

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Main Author: Tan, Kai Zhe
Format: Thesis
Language:English
Published: 2021
Subjects:
Online Access:http://eprints.usm.my/53654/1/TAN%20KAI%20ZHE%20-%20TESIS.pdf%20cut.pdf
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spelling my.usm.eprints.53654 http://eprints.usm.my/53654/ Lumen Maintenance And Trend Predictions For Light-Emitting Diodes Using Regression Analysis Tan, Kai Zhe QA1 Mathematics (General) This study aims to improve the prediction of lumen maintenance life under different thermal-electrical conditions and the Eyring model is proposed in this study. The model parameters are determined by regression approach, which provides the goodness of fit of the prediction model as well as the prediction interval. Apart from this, a method to predict lumen depreciation trend for different operating conditions based on the Eyring model and regression approach is also established. The findings show that the lumen maintenance life and lumen depreciation trend predicted by the Eyring model are more accurate compared to the predictions made by Arrhenius equation and Black’s model. 2021-01 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/53654/1/TAN%20KAI%20ZHE%20-%20TESIS.pdf%20cut.pdf Tan, Kai Zhe (2021) Lumen Maintenance And Trend Predictions For Light-Emitting Diodes Using Regression Analysis. Masters thesis, Universiti Sains Malaysia.
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic QA1 Mathematics (General)
spellingShingle QA1 Mathematics (General)
Tan, Kai Zhe
Lumen Maintenance And Trend Predictions For Light-Emitting Diodes Using Regression Analysis
description This study aims to improve the prediction of lumen maintenance life under different thermal-electrical conditions and the Eyring model is proposed in this study. The model parameters are determined by regression approach, which provides the goodness of fit of the prediction model as well as the prediction interval. Apart from this, a method to predict lumen depreciation trend for different operating conditions based on the Eyring model and regression approach is also established. The findings show that the lumen maintenance life and lumen depreciation trend predicted by the Eyring model are more accurate compared to the predictions made by Arrhenius equation and Black’s model.
format Thesis
author Tan, Kai Zhe
author_facet Tan, Kai Zhe
author_sort Tan, Kai Zhe
title Lumen Maintenance And Trend Predictions For Light-Emitting Diodes Using Regression Analysis
title_short Lumen Maintenance And Trend Predictions For Light-Emitting Diodes Using Regression Analysis
title_full Lumen Maintenance And Trend Predictions For Light-Emitting Diodes Using Regression Analysis
title_fullStr Lumen Maintenance And Trend Predictions For Light-Emitting Diodes Using Regression Analysis
title_full_unstemmed Lumen Maintenance And Trend Predictions For Light-Emitting Diodes Using Regression Analysis
title_sort lumen maintenance and trend predictions for light-emitting diodes using regression analysis
publishDate 2021
url http://eprints.usm.my/53654/1/TAN%20KAI%20ZHE%20-%20TESIS.pdf%20cut.pdf
http://eprints.usm.my/53654/
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score 13.211869