Research of Energy Consumption Prediction of Paper Enterprises Based on GA-BP Neural Network Algorithm

DOI

10.2991/emim-17.2017.127How to use a DOI?

Keywords

Energy management system; B. Data; BP neural network; Genetic algorithm; Weights and Threshold

Abstract

Aiming at the problem of high energy consumption and low utilization rate and low energy consumption management in paper making industry, The Energy management system (EMS)of based on SIEMENS B. Data software is proposed. Because BP neural network has its own defects, which leads to the problem of inaccurate prediction model. In order to obtain the optimum network model, using genetic algorithm to optimize BP neural network weights and threshold. Simulation results show that: GA-BP neural network model has the advantages of high speed and high precision. The energy management system has been successfully applied to a paper making industry in Shandong, and the system has the functions of monitoring and management, energy consumption data analysis and prediction, energy network optimization. The system can meet the requirements of energy management and energy saving in papermaking enterprises.

Copyright

© 2017, 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  - Yanan Hu
AU  - Jiaofei Huo
AU  - Pengwen Wang
PY  - 2017/04
DA  - 2017/04
TI  - Research of Energy Consumption Prediction of Paper Enterprises Based on GA-BP Neural Network Algorithm
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
PB  - Atlantis Press
SP  - 630
EP  - 634
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-17.2017.127
DO  - 10.2991/emim-17.2017.127
ID  - Hu2017/04
ER  -