Regional Industrial Water Demand Prediction Based on Improved Series Gray Neural Network

DOI

10.2991/mic-15.2015.19How to use a DOI?

Keywords

Industrial water demand forecasting; series gray neural network; Nanjing

Abstract

The advantages of nonlinear adaptive gray theory weaken the ability of information processing data sequence-specific volatility and neural networks to construct an improved series gray neural network model system to Nanjing industrial water demand for the study, from 2000 to 2009 data as training samples of water, with water consumption data from 2009 to 2011 to test the model, the results show that the improved prediction series gray neural network model has higher precision and is a practical, strong prediction method finally predicted Nanjing 2015 ~ 2016 industrial water demand.

Copyright

© 2015, 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  - Hu Zhen-Yun
AU  - Chen Zhi-Ming
AU  - Wei Zhang
PY  - 2015/08
DA  - 2015/08
TI  - Regional Industrial Water Demand Prediction Based on Improved Series Gray Neural Network
BT  - Proceedings of the 2nd International Conference on Modelling, Identification and Control
PB  - Atlantis Press
SP  - 85
EP  - 90
SN  - 1951-6851
UR  - https://doi.org/10.2991/mic-15.2015.19
DO  - 10.2991/mic-15.2015.19
ID  - Zhen-Yun2015/08
ER  -