The Application of Gray Model and BP Artificial Neural Network in Predicting Drought in the Liaoning Province

DOI

10.2991/rac-16.2016.44How to use a DOI?

Keywords

Gray Model; BP artificial neural network; precipitation prediction

Abstract

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.

Copyright

© 2016, 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  - 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  - Proceedings of the 7th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention
PB  - Atlantis Press
SP  - 276
EP  - 279
SN  - 1951-6851
UR  - https://doi.org/10.2991/rac-16.2016.44
DO  - 10.2991/rac-16.2016.44
ID  - Liu2016/11
ER  -