location: Current position: Home >> Scientific Research >> Paper Publications

Real time prediction for converter gas tank levels based on multi-output least square support vector regressor

Hits:

Indexed by:期刊论文

Date of Publication:2012-12-01

Journal:CONTROL ENGINEERING PRACTICE

Included Journals:Scopus、SCIE、EI

Volume:20

Issue:12

Page Number:1400-1409

ISSN No.:0967-0661

Key Words:LDG system; Gas tank level; Multi-output LSSVM; Regression prediction; Parameter optimization

Abstract:Linz Donawitz converter gas (LOG) is the significant secondary energy resource that plays a crucial role in the energy system of steel industry. Since the real-time prediction for the gas tank level of LOG system is the foundation of energy balance scheduling that directly affects the energy costs of enterprise, more and more attentions has been paid to this issue. In this study, taking the LOG system of Ma'anshan Steel Co., Ltd, China into account, a multi-output least square support vector regressor is proposed, which considers not only the single fitting error of each tank level but also the combined one. Then, a prediction model for the multi-tank LOG system is derived, and a particle swarm optimization is designed to determine the parameters of this model for the sake of improving the prediction accuracy. The experimental results based on the real data from the plant demonstrate that the proposed method is effective to the practical application. (c) 2012 Elsevier Ltd. All rights reserved.

Pre One:发挥科研团队综合优势,提高研究生培养质量-以控制科学与工程学科为例

Next One:Effective Noise Estimation-Based Online Prediction for Byproduct Gas System in Steel Industry