Application of Decision Tree and Neural Network Algorithm in Water Quality Assessment Forecast

DOI

10.2991/icmsa-15.2015.137How to use a DOI?

Keywords

Neural Network, Decision Tree, Water Quality Model.

Abstract

The paper builds water quality assessment forecast model by adopting four algorithms which are decision tree, BP neural network, Logistic recursion and RBF neural network and analyzes the result. The forecast result shows that RBF neural network is the fittest method and its rate of accuracy is high that can be used widely.

Copyright

© 2015, 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  - Bing-Xiang Liu
AU  - Xiang Wan
AU  - Xu-Dong Wu
AU  - Ying-Xi Li
AU  - Hui-Qiu Zhu
PY  - 2014/06
DA  - 2014/06
TI  - Application of Decision Tree and Neural Network Algorithm in Water Quality Assessment Forecast
BT  - Proceedings of the 2015 International Conference on Material Science and Applications
PB  - Atlantis Press
SP  - 747
EP  - 751
SN  - 2352-541X
UR  - https://doi.org/10.2991/icmsa-15.2015.137
DO  - 10.2991/icmsa-15.2015.137
ID  - Liu2014/06
ER  -