Rain fall predict and comparing research based on Arcgis and BP neural network

DOI

10.2991/icmemtc-16.2016.291How to use a DOI?

Keywords

Arcgis; BP algorithms; Rainfall forecasting; Kriging interpolation; Error analysis

Abstract

Based on the data of the rainfall from 24 base stations on the area of Chao River Basin in the near 54 years(range from 1958 to 2012) , the estimation is carried out by using Arcgis kriging interpolation and BP algorithms. And try to do the error analysis and the consequences comparing of these two results in the use of statistical approach. It is surely an innovative study which applies the advanced mathematical method in the rainfall research in the environmental field. After a serious of complicated data processing, the final conclusion is that it is feasible to apply BP neural network model to the forecast of rainfall, which is the correct method with high accuracy rate.

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  - Zimo Guan
AU  - Ziyu Tian
AU  - Yushi Xu
AU  - Han Dai
PY  - 2016/04
DA  - 2016/04
TI  - Rain fall predict and comparing research based on Arcgis and BP neural network
BT  - Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control
PB  - Atlantis Press
SP  - 1509
EP  - 1514
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmemtc-16.2016.291
DO  - 10.2991/icmemtc-16.2016.291
ID  - Guan2016/04
ER  -