Multivariate time series forecast in industrial process based on XGBoost and GRU

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 数字工厂研究室

	Multivariate time series forecast in industrial process based on XGBoost and GRU
	Zhai NJ(翟乃举)1,2,3,5; Yao PF(姚培福)4; Zhou XF(周晓锋)1,2,3
	2020
会议日期	December 11-13, 2020
会议地点	Chongqing, China
关键词	time series multivariate Xgboost model GRU model temperature of the heating furnace
页码	1397-1400
英文摘要	In this paper, a time series prediction model that merges eXtreme Gradient Boosting (XGBoost) and Gate Recurrent Unit (GRU), XGB-GRU model, is proposed for multivariate time series prediction in industry. The XGB-GRU model uses XGBoost's strong feature extraction capabilities to extract the hidden information of multiple control variables in industrial data. Next, the model uses GRU's unique gating unit to extract the timing information in the industrial data. Finally, the importance of XGBoost output variables to guide actual production and solve the problem of inexplicability of neural networks. Predicting the temperature of the heating furnace verifies that the proposed XGB-GRU is better than a single XGBoost and GRU model. And the model has a good fit to the predicted value.
源文献作者	Chengdu Global Union Academy of Science and Technology ; Chongqing Geeks Education Technology Co., Ltd ; Chongqing Global Union Academy of Science and Technology ; Chongqing Jiaotong University ; IEEE Beijing Section
产权排序	1
会议录	2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference
会议录出版者	IEEE
会议录出版地	New York
语种	英语
ISBN号	978-1-7281-5244-8
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/28322]
专题	沈阳自动化研究所_数字工厂研究室
通讯作者	Zhou XF(周晓锋)
作者单位	1.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China 2.Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang, China 3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 4.China Copper Co.LTD, Kunming, China 5.University of Chinese Academy of Sciences, Beijing, China
推荐引用方式 GB/T 7714	Zhai NJ,Yao PF,Zhou XF. Multivariate time series forecast in industrial process based on XGBoost and GRU[C]. 见:. Chongqing, China. December 11-13, 2020.