Paper Title:
Supply and Demand Forecasting of Blast Furnace Gas Based on Artificial Neural Network in Iron and Steel Works
  Abstract

Abstract.Blast Furnace Gas (BFG) system of an iron and steel works was considered. The relationship of gas amount and factors about BFG generation and consumption was analyzed by grey correlationand the BP neural network prediction model of blast furnace gaswas established based on artificial neural network for forecasting thesupply and demandof BFGinthe iron and steel-making processes.The scientific forecasting of BFG generation and consumption in each process was discussed undernormal production and accidental maintenance condition. The results show that established forecasting model is high precision, small errors, and can solve effectively actual production of BFG prediction problem and decreasing BFG flare, providing theoretical basis for establishing reasonable plans in the iron and steel works.

  Info
Periodical
Advanced Materials Research (Volumes 443-444)
Chapter
Chapter 1: Advances in Manufacturing Engineering Techniques and Materials Science
Edited by
Li Jian
Pages
183-188
DOI
10.4028/www.scientific.net/AMR.443-444.183
Citation
Q. Zhang, Y. L. Gu, W. Ti, J. J. Cai, "Supply and Demand Forecasting of Blast Furnace Gas Based on Artificial Neural Network in Iron and Steel Works", Advanced Materials Research, Vols. 443-444, pp. 183-188, 2012
Online since
January 2012
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Price
$32.00
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