Predictive Model of Energy Cost in Steelmaking Process Based on BP Neural Network

DOI

10.2991/sekeie-14.2014.18How to use a DOI?

Keywords

Component;Neural network; Genetic algorithm; Cost control; Steel making; BP optimizing; Energy cost

Abstract

China is a Steel superpower, with large production and high efficiency. But we need more research in Business energy cost control. This paper is oriented to cost flow of steel industry, Aim at solve the shorting of energy cost control in steel industry. Using the producing data in steel making, Basing on BP neural network, optimizing by Genetic algorithm, I build the Predictive Model which has a better predict result and provide predict function for steel industry. It make business management more convenient, support the task of energy-saving. Mean while, it has validate that Genetic algorithm has good function in BP neural network’s optimizing problem and can be used in practical problems.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhenchao Bai
AU  - Gang Wei
AU  - Xianhui Liu
AU  - Weidong Zhao
PY  - 2014/03
DA  - 2014/03
TI  - Predictive Model of Energy Cost in Steelmaking Process Based on BP Neural Network
BT  - Proceedings of the 2nd International Conference on Software Engineering, Knowledge Engineering and Information Engineering (SEKEIE 2014)
PB  - Atlantis Press
SP  - 77
EP  - 80
SN  - 1951-6851
UR  - https://doi.org/10.2991/sekeie-14.2014.18
DO  - 10.2991/sekeie-14.2014.18
ID  - Bai2014/03
ER  -