Application of Temperature Prediction Model Based on LSTNet in Telecommunication Room

被引：3

作者：

Lee, Chun-Hsiang ^{[1
]}

Yang, Saisai ^{[1
]}

Fan, Yongqiang ^{[2
]}

Lin, Xiunao ^{[1
]}

Tao, Hongfeng ^{[1
]}

Wu, Chao ^{[3
]}

机构：

[1] Zhejiang Post & Telecom Engn Construct Co Ltd, 170 Kaixuan Rd, Hangzhou, Zhejiang, Peoples R China

[2] Hangzhou Hanggang Cloud Comp Data Ctr Co Ltd, 132 Shenjiaqiao Rd, Hangzhou, Zhejiang, Peoples R China

[3] Zhejiang Univ, Hangzhou, Zhejiang, Peoples R China

来源：

2020 5TH INTERNATIONAL CONFERENCE ON MATHEMATICS AND ARTIFICIAL INTELLIGENCE (ICMAI 2020) | 2020年

关键词：

Temperature prediction system; Online learning; LSTNet; FTRL;

D O I：

10.1145/3395260.3395270

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we present an application of a temperature prediction model based on the Long- and Short-term Time-series network (LSTNet). The model allows predicting the indoor temperature for the next 20 to 60 minutes based on the operating status of the telecommunications room and the outdoor weather condition. In addition, we propose a mechanism for the automatic model update that is triggered when the accuracy of the prediction model is reduced or when the telecommunications room equipment is replaced.

引用

页码：114 / 118

页数：5

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