Title :
A kind of classification method for evaluating water qualities
Author :
Gao Qianqian ; Zhang Ying
Author_Institution :
Coll. of Inf. Eng., Shanghai Maritime Univ., Shanghai, China
Abstract :
Evaluation of water quality based on monitoring data and intelligent information processing algorithm has great significance for the management of lake resources. For the classification of water quality of Chaohu, Random Forest algorithm was used to evaluate the classification of the water quality of this area. Compared with some typical data-driven methods, this method has higher precision of classification and better tolerance of noise. The experiment result shows that the accuracy rate of water quality classification in Hubin monitoring section can reach 96.15%, and the accuracy rate of water quality classification in Yu Xikou monitoring section can reach 100%. The RF method has higher classification accuracy, fine stability and generalization.
Keywords :
environmental science computing; pattern classification; water quality; classification method; intelligent information processing algorithm; lake resources management; random forest algorithm; water quality classification; water quality evaluation; Accuracy; Classification algorithms; Decision trees; Lakes; Monitoring; Radio frequency; Water resources; Classification; Decision-making tree; Evaluation; Random forest algorithm;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7162658