Rain fall predict and comparing research based on Arcgis and BP neural network
Authors
Zimo Guan, Ziyu Tian, Yushi Xu, Han Dai
Corresponding Author
Zimo Guan
Available Online April 2016.
- 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/).
Cite this article
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 -