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研究生:蔡承旻
研究生(外文):TSAI, CHENG-MIN
論文名稱:利用環境與氣候因素建立兩階段預測模式在空氣品質預測的應用
論文名稱(外文):The Application of Two-Stage Prediction Model in Air Quality Prediction is Established Based on Environmental and Climatic Factors
指導教授:鄭景俗鄭景俗引用關係
指導教授(外文):CHENG, CHING-HSUE
口試委員:鄭景俗陳重臣王佳文
口試委員(外文):CHENG, CHING-HSUECHEN,CHONG-CHENWANG,JIA-WUN
口試日期:2020-05-13
學位類別:碩士
校院名稱:國立雲林科技大學
系所名稱:資訊管理系
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:中文
論文頁數:51
中文關鍵詞:空氣汙染屬性選取分類空氣汙染規則空氣污染預測
外文關鍵詞:Air PollutionFeature SelectionClassificationRulesPrediction
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空氣污染嚴重影響著日常生活品質及健康問題,快速工業化及城市發展是空氣汙染的主要原因,如何平衡工業化和城市發展與空氣品質是各國面臨的巨大挑戰。在本研究中,選取了來自台灣行政院環境保護署的交通環境監測站及工業環境監測站2017年的觀測資料,利用多種環境因素(二氧化硫、一氧化碳、臭氧、懸浮微粒、細懸浮微粒、氮氧化物、一氧化氮、二氧化氮、總碳氫合物、非甲烷碳氫化合物、及甲烷)及氣候因素(大氣溫度、雨量、相對溼度、及風速)作為研究變數。第一階段透過屬性選取方法找出重要的因素並使用四種分類器(Decision Tree、Random Forest、Random Tree、Tree C4.5 )來找出影響空氣品質的規則。第二階段將第一階段產生規則中重要的汙染源當作預測變數,使用4種預測方法(Random Forest、Random Tree、Extra Trees、SVR)建立預測模型並評估模型的效果,實驗結果表明Random Forest在屬性選後的分類及預測準確度的績效較佳,本研究結果將提供給相關所有人做參考,便於針對特定環境因素做出應對策略。
Air pollution seriously affects the quality of daily life and health problems. Rapid industrialization and urban development are the main causes of air pollution. In this study, selected the traffic from the environmental protection administration, executive yuan of Taiwan environmental monitoring station and industrial environmental monitoring station observation data in 2017, using a variety of environmental factors (SO2、CO、O3、PM10、PM2.5、NOx、NO、NO2、THC、NCHN、CH4) and climate factors (Air temperature, Rainfall, humidity, and wind speed) as the research variables. In the first stage, important factors were found through the attribute selection method and four classifiers (Decision Tree, Random Forest, Random Tree, and Tree C4.5) were used to find the rules affecting air quality. The second phase will generate rules in the first phase of the important pollution sources as prediction variables, using 4 kinds of forecasting methods ( Random Forest, Random Tree, Extra Trees, SVR) prediction model is set up and evaluate the effect of the model, the experimental results show that the Random Forest in the classification and properties prediction accuracy of performance better, this study will provide a reference for everyone to do, to make strategy for specific environmental factors.
摘要 i
Abstract ii
目錄 iii
表目錄 v
圖目錄 vi
1. 介紹 1
1.1背景 1
1.2 動機及目的 3
1.3 論文結構 5
2. 相關研究 6
2.1 空氣汙染 6
2.2 屬性選取 11
2.2.1 Correlation based feature selection (CFS) 11
2.2.2 Correlation 11
2.2.3 Information Gain 11
2.2.4 Gain Ratio 12
2.2.5 ReliefF 12
2.3 分類及預測技術 13
2.3.1 Tree C4.5 13
2.3.2 Random Forest 13
2.3.3 Random Tree 14
2.3.4 Decision Tree 15
2.3.5 SVR 15
2.3.6 Extra Trees 16
3. 研究方法 17
3.1 概念 17
3.2 提出的研究流程 17
Step 1. 蒐集資料 19
Step 2. 資料前處理 19
Step 3. 屬性選取 20
Step 4. 分類及評估 20
Step 5. 產生規則 21
Step 6. 預測模型 21
4. 實驗結果 22
4.1 實驗環境與資料集 22
4.2 實驗與比較 22
4.2.1 空氣品質4類別實驗比較 23
4.2.2 空氣品質3類別實驗比較 25
4.3 規則產生 27
4.4 預測建模比較 30
4.5 研究發現 31
5. 結論及建議 39
參考文獻 40


行政院環境保護署環境資源資料庫https://erdb.epa.gov.tw/FileDownload/FileDownload.aspx
行政院環境保護署空氣品質監測網https://taqm.epa.gov.tw/taqm/tw/YearlyDataDownload.aspx
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