The Application of Gray Model and BP Artificial Neural Network in Predicting Drought in the Liaoning Province
Xiaojing Liu, Yongpeng Song, Donglai Ma, Peng Chen
Available Online November 2016.
- https://doi.org/10.2991/rac-16.2016.44How to use a DOI?
- Gray Model; BP artificial neural network; precipitation prediction
- Precipitation prediction is the core of a regional drought prediction. Due to the great randomness and uncertainty in the precipitation process, this study combined the grey model and BP artificial neural network. The residual errors of precipitation were modified by the BP artificial neural network after the precipitation were modeled and predicted by the grey model, then the grey-BP neural network combination model was established for predicting the precipitation in the studied area. The results showed that the prediction accuracy of the combination model was the highest by integrating the advantages of the grey model and BP artificial neural network. The prediction error of the combination model was much lower than the grey model's and only slightly lower than the BP neural network model's.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Xiaojing Liu AU - Yongpeng Song AU - Donglai Ma AU - Peng Chen PY - 2016/11 DA - 2016/11 TI - The Application of Gray Model and BP Artificial Neural Network in Predicting Drought in the Liaoning Province BT - 7th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC-2016) PB - Atlantis Press SP - 276 EP - 279 SN - 1951-6851 UR - https://doi.org/10.2991/rac-16.2016.44 DO - https://doi.org/10.2991/rac-16.2016.44 ID - Liu2016/11 ER -