Research on Thermal Effect of Power LED Devices Based on PCA and Neural Network

被引：0

作者：

Yan Qiyan ^{[1
]}

机构：

[1] Guangdong Univ Sci & Technol, Mech & Elect Engn Dept, Dongguan 523083, Peoples R China

来源：

2017 29TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2017年

关键词：

PCA; BP Neural Network; Power LED Devices; Thermal Effect; Reliability;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a method to predict the thermal effect of the power LED based on principal component analysis (PCA) and BP neural network. This method adopts PCA for processing the sample data of the power LED, and then the processed data samples are considered as the input of BP neural network. Through this data processing the number of the input variables can be reduced and the BP network structure is simplified. The predicting experiment show that this method has strong adaptability and robustness. The method is used to predict the thermal effect of the power LED devices produced by APT Electronics LTD., and the prediction error is less than 5%.

引用

页码：4324 / 4327

页数：4

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