An analyzing method for chemical classifications of groundwater based on the Bayes Discriminant Theory
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DOI:10.7606/j.issn.1000-7601.2015.04.37
Key Words: Inner Mongolia Hetao Irrigation District  chemical type of groundwater  Bayes discriminant  classification
Author NameAffiliation
LI Bin 内蒙古农业大学水利与土木建筑工程学院 内蒙古 呼和浩特 010018内蒙古农牧业科学院资源环境与检测技术研究所 内蒙古 呼和浩特 010031 
SHI Hai-bin 内蒙古农业大学水利与土木建筑工程学院 内蒙古 呼和浩特 010018 
LI Zhen 内蒙古农业大学水利与土木建筑工程学院 内蒙古 呼和浩特 010018 
ZHANG Jian-guo 巴彦淖尔市水利科学研究所 内蒙古 巴彦淖尔 015000 
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Abstract:
      Bayes discriminant analysis method was applied into the discrimination and classification of groundwater chemical types to set up a Bayes discriminant analysis model for synthetic evaluation of groundwater chemical types. Six indexes including Na++K+、Ca2+、Mg2+、HCO-3、Cl-、SO42- were selected as the differentiation parameters in this model. Chemicals in the groundwater could be classified into three types that were chosen as the three normal populations for Bayes discriminant analysis. Groundwater in Hetao irrigation district was utilized as the trial sample for data collection to set up the linear discriminant function of Bayes. The Bayesian linear discriminant function was then employed to calculate and determine the Bayes discriminant function values of the samples. The population with the maximal value was thereby used as the population for entire samples. Finally, in order to test the validity of this model, the cutting ring method was applied to evaluate the discriminate criterion. Results of this research showed that the misjudgment rate of this Bayes discriminant analysis model was low, reaching as high as 82.5% in correct recognition rate and 86.6% in output accuracy. Compared with traditional method, this Bayes discriminant analysis model could provide classification outcome that was clear and informative information for chemicals in water.