Use of finite mixture model to analyze the variability of heavy metal pollution characteristics in peitou guandu area

Guey Shin Shyu, Tsun Kuo Chang, Pei Hsun Yao, Ching Ming Wang, Wei Ta Fang, Ming Lin Hsu

研究成果: 雜誌貢獻文章

摘要

Statistical method is a tool with which we can use to explain and employ the sample data. In recent years, the development of GIS has made the improvement of combination of statistical methods and spatial relationship. Finite Mixture Model (FMM) has the ability to classify objectively the data by unsupervised learning. Then cooperating with spatial analysis, we can get implicit causes and characteristics of data to increase efficiently the data value. In this paper, Finite Mixture Model was used to classify heavy metal pollution source characteristics in the Peitou Guandu Area.

原文英語
頁(從 - 到)15-26
頁數12
期刊Journal of Taiwan Agricultural Engineering
63
發行號4
出版狀態已發佈 - 2017 十二月

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Engineering(all)

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