The forest fire prediction in JiangXi province based on PSO-GA-BP neural network

DOI

10.2991/wartia-16.2016.270How to use a DOI?

Keywords

Forest fire danger rating, Meteorological factors, PSO-GA-BP neural network,

Abstract

In this paper, we collected the meteorological data and forest fire danger rating data of four stations in JiangXi (NanChang, JingDeZhen, GiAn, GanZhou) from 2013 to 2015, and build a neural network fire prediction model. Then use GA, PSO and PSO-GA hybrid algorithm to improve BP neural network.By contrasting the prediction results of BP network, GA-BP network, PSO-BP network and PSO-GA-BP network, the prediction accuracy of PSO-GA-BP network is the highest. The result of experiment shows that the effect of BP network optimized by PSO-GA is the best, compared with GA and PSO.

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/).

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TY  - CONF
AU  - Zhijian Yin
AU  - Fan Wang
AU  - TianTian Tang
AU  - Qiang Luo
AU  - Kun Xiang
PY  - 2016/05
DA  - 2016/05
TI  - The forest fire prediction in JiangXi province based on PSO-GA-BP neural network
BT  - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
PB  - Atlantis Press
SP  - 1286
EP  - 1290
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-16.2016.270
DO  - 10.2991/wartia-16.2016.270
ID  - Yin2016/05
ER  -