Application of GA Optimizing Neural Network to Coal Sales Forecasts

DOI

10.2991/icieac-14.2014.32How to use a DOI?

Keywords

coal sales forecast; neural network; BP algorithm; LM algorithm; Genetic algorithm

Abstract

With the rapid development of the market, coal enterprises predict sales by subjective experience, which is far from accurate. In order to minimize decision-making errors, to avoid warehouse inventory shortages or backlog and to increase prediction accuracy of coal sales forecast, the study of forecast methods is particularly important. In the paper, improved BP algorithm is adopted based on some large coal enterprises’ practical characters. Connection weights are optimized by generic algorithm. The forecast method is implemented in the paper. Theoretical analysis and experimental results show that neural network is feasible and effective for coal sales prediction, with a bright future. Genetic algorithm optimizing neural network increases speed calculation and reliability.

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/).

Download article (PDF)

TY  - CONF
AU  - Shuang Zhang
AU  - Hu Qinghe
PY  - 2014/03
DA  - 2014/03
TI  - Application of GA Optimizing Neural Network to Coal Sales Forecasts
BT  - Proceedings of the 2nd International Conference on Information, Electronics and Computer
PB  - Atlantis Press
SP  - 142
EP  - 147
SN  - 1951-6851
UR  - https://doi.org/10.2991/icieac-14.2014.32
DO  - 10.2991/icieac-14.2014.32
ID  - Zhang2014/03
ER  -