Adaptive neuro fuzzy inference system for classification of water quality status  

作　　者：Han Yan,Zhihong Zou,Huiwen Wang School of Economics and Management,Beihang University,Beijing 100191,China 

出　　处：《Journal of Environmental Sciences》2010年第12期1891-1896,共6页环境科学学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(No. 50778009)

摘　　要：An adaptive neuro fuzzy inference system was used for classifying water quality status of river. It applied several physical and inorganic chemical indicators including dissolved oxygen, chemical oxygen demand, and ammonia-nitrogen. A data set （nine weeks, total 845 observations） was collected from 100 monitoring stations in all major river basins in China and used for training and validating the model. Up to 89.59% of the data could be correctly classified using this model. Such performance was more competitive when compared with artificial neural networks. It is applicable in evaluation and classification of water quality status.An adaptive neuro fuzzy inference system was used for classifying water quality status of river. It applied several physical and inorganic chemical indicators including dissolved oxygen, chemical oxygen demand, and ammonia-nitrogen. A data set （nine weeks, total 845 observations） was collected from 100 monitoring stations in all major river basins in China and used for training and validating the model. Up to 89.59% of the data could be correctly classified using this model. Such performance was more competitive when compared with artificial neural networks. It is applicable in evaluation and classification of water quality status.

关 键 词：adaptive neuro fuzzy inference system artificial neural networks water quality status CLASSIFICATION 

分 类 号：X832[环境科学与工程—环境工程]