JOURNAL OF YANGTZE RIVER SCIENTIFIC RESEARCH INSTI ›› 2012, Vol. 29 ›› Issue (9): 91-94.DOI: 10.3969/j.issn.1001-5485.2012.09.021

• TECHNICAL NOTES • Previous Articles     Next Articles

Application of R Language Based Data Mining in Water Environment Management

XIAO Kai1,  WEI Fei2,  PENG Chang-shui3   

  1. 1.Network Information Center of Changjiang Water Resources Commission, Wuhan  430010, China; 2.Agencies Service Center of Changjiang Water Resources Commission, Wuhan  430010, China;3. Information Center, Yangtze River Scientific Research Institute, Wuhan 430010, China
  • Received:2011-06-28 Revised:2012-05-25 Online:2012-09-01 Published:2012-09-13

Abstract: The authors analyzed the model of harmful algal blooms in the river on the basis of classification regression tree (CART) algorithm of data mining. Results indicated that phosphate, chloride and the maximum pH values are key factors of algae generation. Furthermore, we employed the R language to validate the superiority and convenience of using CART algorithm. The conclusions and methods could contribute to a more effective water quality monitoring and forecasting.

Key words: data mining, classification and regression tree (CART), R language, water quality monitoring

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