Estimation of Missing Data of Showcase Using Artificial Neural Networks

被引：0

作者：

Sakurai, Daiji ^{[1
]}

Fukuyama, Yoshikazu ^{[1
]}

Santana, Adamo ^{[2
]}

Kawamura, Yu ^{[3
]}

Murakami, Kenya ^{[3
]}

Iizaka, Tatsuya ^{[3
]}

Matsui, Tetsuro ^{[3
]}

机构：

[1] Meiji Univ, Sch Interdisciplinary Math Sci, Tokyo, Japan

[2] Fed Univ Para, Inst Technol, Belem, Para, Brazil

[3] Fuji Elect Co Ltd, Tokyo, Japan

来源：

2017 IEEE 10TH INTERNATIONAL WORKSHOP ON COMPUTATIONAL INTELLIGENCE AND APPLICATIONS (IWCIA) | 2017年

关键词：

Estimation of missing data; Time series data; Artificial Neural Network(ANN);

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes an estimation method of missing data of showcase using Artificial Neural Networks (ANN). When various abnormal conditions such as frost formation in the refrigerators and refrigerant leakage happen, vendors of showcases have to treat the abnormal conditions as quickly as possible. Therefore, various measured data of showcases such as temperatures or pressures of some portions of showcases have to be gathered correctly and symptoms of the abnormal conditions should be estimated in advance. However, in rare cases, there is a possibility to miss to gather the data due to various on-site conditions. The proposed method is applied to missing data of actual showcases. Effectiveness of the proposed method is verified by comparison with a conventional ARMA method.

引用

页码：15 / 18

页数：4

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