Using Data Mining Techniques to Identify Enterprises with High Water Pollution Potential
學年 108
學期 1
發表日期 2019-10-18
作品名稱 Using Data Mining Techniques to Identify Enterprises with High Water Pollution Potential
作品名稱（其他語言）
著者 H.C. Lo; Y.Y. Huang; L.S. Hu
作品所屬單位
出版者
會議名稱 CIE49 conference
會議地點 Beijing, China
摘要 To stop environmental pollution caused by improper wastewater discharges, the related enterprises are required to regularly report the water monitoring data via Internet. To make sure the data submitted are in good quality, the inspectors are arranged to carry out the checkup on site either through random samplings or the appeals and reports from the public. Those enterprises violating the regulations thus make improvements as per the inspection results. However, in view of the limited manpower, the environmental control institutions will not be able to detect all the violators immediately if simply random samplings are applied. It is, therefore, an important issue to effectively and at the primal time to single out the enterprises with high water pollution potential. Using scientific data analysis, this paper aims to identify these targeting enterprises and construct a pollution warning model. Current report data on the Internet will be employed for statistic and data mining analysis, such as logistic regression and neural network. Meanwhile, comparisons will also be made concerning the validities of these warning models, hoping to better choose the appropriate one. The study findings can be used as basis for environmental control institutions while establishing pollution warning web portals so that the enforcement authorities can keep good track of the potential targets in advance and thus enhance the accuracy of the inspection.
關鍵字 Industrial Waste Pollution;Logistic Regression;Neural Network
語言 en
收錄於
會議性質 國際
校內研討會地點 無
研討會時間 20191018~20191021
通訊作者
國別 CHN
公開徵稿
出版型式
出處
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/118372 )

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