Indexed by:会议论文

First Author:Liu, Ying

Co-author:Zhao, Jun,Wang, Wei,Sheng, Chun-yang,Cong, Li-qun,Feng, Wei-min

Date of Publication:2010-01-01

Included Journals:EI、CPCI-S、Scopus

Document Type:A

Page Number:4446-4451

Key Words:prediction method for generation and consumption of coke oven; empirical mode decomposition; echo state network; direct prediction method

Abstract:A direct prediction method based on empirical mode decomposition and echo state network is proposed to predict coke oven gas generation and consumption of the steel industry. First, the empirical mode decomposition is used to de-noise the practical data with high noise level. Then the direct relationship between the prediction origin and prediction horizon using echo state network is established without the need to close the network loop or iterate in the prediction process. Such a method has the advantage of avoiding the iteration error accumulation, and the corresponding forecasting precision is increased. The prediction results using practical production data show the validity of the proposed method and provide the scientific decision support for the gas resources scheduling.

Translation or Not:no