论文类型：期刊论文

第一作者：Liu Y.

通讯作者：Zhao, J.; Research Center of Information and Control, Dalian University of Technology, Dalian, 116024, China; email: zhaoj@dlut.edu.cn

合写作者：Zhao J.,Wang W.

发表时间：2010-08-01

发表刊物：ICIC Express Letters

收录刊物：EI、Scopus

文献类型：J

卷号：4

期号：4

页面范围：1373-1378

ISSN号：1881803X

摘要：Coke oven gas is one of the most important byproduct energy in steel industry. The real-time prediction for the amount of generation and consumption of COG is a very significant problem. A prediction method based on time series is proposed in this paper, where an improved echo state network combined with Gaussian process, instead of using linear regression in traditional echo state network, is established. This method makes inferences about the relationship between the reservoir states and networks output using Gaussian process in order to eliminate the ill condition of the model. The experimental results using practical data demonstrate the proposed approach exhibits high prediction precision and can provide effective probability estimation for the prediction. ICIC International ? 2010 ISSN 1881-803X.

是否译文：否