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  • 标题:Hybrid Method Air Quality Classification Analysis Model
  • 本地全文:下载
  • 作者:Musli Yanto ; Syafri Arlis ; Jufriadif Na’am
  • 期刊名称:TEM Journal
  • 印刷版ISSN:2217-8309
  • 电子版ISSN:2217-8333
  • 出版年度:2022
  • 卷号:11
  • 期号:2
  • 页码:829-836
  • DOI:10.18421/TEM112-41
  • 语种:English
  • 出版社:UIKTEN
  • 摘要:This paper aims to present a discussion of air quality based on the classification analysis developed by hybrid method. Problems that occur, where the longer the air quality is getting worse and can cause serious problems for human life. The method in performing the used analysis consisted of K-Means clustering, Multiple Linear Regression (MRL), Artificial Neural Network (ANN), and Decision Tree Algorithm C.45. The results of MRL measurement show that correlation relationship is the same as the variable with an output of 70.7%. Then the results of determination with ANN showed an MSE value of 0.0018197 and output accuracy of 99.99%.
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