Application of GA Optimizing Neural Network to Coal Sales Forecasts
Shuang Zhang, Hu Qinghe
Available Online March 2014.
- https://doi.org/10.2991/icieac-14.2014.32How to use a DOI?
- coal sales forecast; neural network; BP algorithm; LM algorithm; Genetic algorithm
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - https://doi.org/10.2991/icieac-14.2014.32 ID - Zhang2014/03 ER -