跳到主要內容

臺灣博碩士論文加值系統

(44.210.99.209) 您好!臺灣時間:2024/04/16 03:06
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:張展維
研究生(外文):ZHENG,ZHEN-WEI
論文名稱:車流量與空氣細懸浮微粒相關性分析
論文名稱(外文):Exploring the Relationship between the Traffic Flow and the Ambient Particulate Matter 2.5 Concentration
指導教授:戴榮賦戴榮賦引用關係
指導教授(外文):DAY,RONG-FUH
口試委員:陳彥錚廖士寬
口試委員(外文):CHEN,YEN-CHENGLIAO,SHIH-KUAN
口試日期:2017-07-25
學位類別:碩士
校院名稱:國立暨南國際大學
系所名稱:資訊管理學系
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:2017
畢業學年度:105
語文別:中文
論文頁數:24
中文關鍵詞:空汙PM2.5影像處理車流量
外文關鍵詞:Air pollutionPM2.5Image processingTraffic flow
相關次數:
  • 被引用被引用:4
  • 點閱點閱:539
  • 評分評分:
  • 下載下載:9
  • 收藏至我的研究室書目清單書目收藏:0
本研究有鑑於台灣空汙議題不斷地延燒,而專家指出有7成的污染都來自境內,但都無法明確的指出汙染源,所以本研究針對境內主要汙染源之一的車輛廢氣排放,來做偵測來研究車流量與PM2.5的相關性分析。本研究應用影像處理技術即時追蹤路上的車流量,並且同時偵測路上的PM2.5的濃度了解兩者的相關性。
不分組的整體數據呈現顯著中度相關,相關性r值為0.338,表示車流量對PM2.5有一定的影響力。根據環保署每日空氣品質指標(Daily Air Quality Index, DAQI)的細懸浮微粒(PM2.5)預警濃度分級,而24 μg/m3 - 35 μg/m3為第三級距,超過此級距以上就會達到警示標準,故以此級距來區分濃度分嶺的標準。將數據區分為高濃度與低濃度組時,高濃度組的相關性r值為0.433,較不分組時相關性更高,而低濃度組卻無顯著相關。低濃度組不相關的可能原因是,數據的收集時前一兩日有下過大雨,當時PM2.5數值都在10 μg/m3以下。
The issue of air pollution continues in Taiwan. Experts have pointed out that 70% of the sources of pollution come within the territory, but they cannot be accurately identified. Therefore, this study detected the exhaust emissions of vehicles, one of the major sources of pollution in Taiwan, to adopt a correlation analysis of traffic flow and PM2.5. It applied image processing technique to supervise real-time traffic flow, and it also detected the PM2.5 concentration on the road to understand the correlation between the two.
The ungrouped overall data were of significant moderate correlation, and value R was 0.338, which showed that traffic flow had a certain impact on PM2.5. According to the PM2.5 Warning Concentration Grading Standard in the Daily Air Quality Index (DAQI) published by the Environmental Protection Administration, the third class interval was from 24 μg/m3 to 35 μg/m3. It would reach the warning standard once it was above the third class interval, which was therefore used as the standard to differentiate the concentration. After dividing the data into high concentration and low concentration, it was shown that the value R of the high concentration group was 0.433, which was higher than that of the ungrouped data, while the low concentration group did not show significant correlation. The possible reason to explain the non-correlation was that there had been heavy rain one or two days before data collection. The PM2.5 at that time was under 10 μg/m3.
摘要 i
Abstract ii
目次 iii
表目次 v
圖目次 vi
第一章 緒論 1
第一節 研究動機 1
第二節 研究問題與範圍 3
1、 訓練辨識車輛分類器 3
2、 車流量與空氣品質的相關性 3
第二章 文獻探討 4
第一節 懸浮微粒 (particulate matter) 4
1 . 懸浮微粒定義 4
2. 懸浮微粒來源 4
3. 懸浮微粒對健康影響 6
第二節 電腦視覺文獻探討 7
1. 何謂電腦視覺 7
2. 電腦視覺相關應用 7
3. OpenCV 函式庫 (Open Source Computer Vision Library) & EMGU CV 7
4. 哈爾特徵(Haar-like features) 9
第三章 研究方法 11
第一節 系統開發環境 11
第二節 系統架構 12
第三節 分類器訓練 13
1. 正負樣本收集 13
2. 創建正負樣本描述文件 14
3. 創建正樣本向量描述文件 15
4. 訓練分類器 16
5. 辨識準確率 16
第四節 系統畫面 17
1. 畫面顯示 17
2. 數據顯示 17
第五節 系統流程 18
第六節 實驗流程 18
1. 實驗地點. 18
2. 實驗時間 18
3. 數據分析 18
第四章 資料分析 19
第一節 樣本不分組車流量與細懸浮微粒相關性分析 19
第二節 樣本以24 μg/ m3 濃度為標準分為高濃度與低濃度組 20
第五章 結論與建議 22
第一節 研究發現 22
第二節 研究限制 22
第三節 未來研究 22
參考文獻 23
Boldo, E., Medina, S., Le Tertre, A., Hurley, F., Mücke, H.-G., Ballester, F., & Aguilera, I. (2006). Apheis: Health Impact Assessment of Long-term Exposure to PM2.5 in 23 European Cities. European Journal of Epidemiology, 21(6), 449-458. doi: 10.1007/s10654-006-9014-0
Dockery , D. W., Pope , C. A., Xu , X., Spengler , J. D., Ware , J. H., Fay , M. E., . . . Speizer , F. E. (1993). An Association between Air Pollution and Mortality in Six U.S. Cities. New England Journal of Medicine, 329(24), 1753-1759. doi: 10.1056/nejm199312093292401
Fan, Z., Meng, Q., Weisel, C., Laumbach, R., Ohman-Strickland, P., Shalat, S., . . . Black, K. (2009). Acute exposure to elevated PM(2.5) generated by traffic and cardiopulmonary health effects in healthy older adults. Journal of exposure science & environmental epidemiology, 19(5), 525-533. doi: 10.1038/jes.2008.46
Hodi , F. S., O'Day , S. J., McDermott , D. F., Weber , R. W., Sosman , J. A., Haanen , J. B., . . . Urba , W. J. (2010). Improved Survival with Ipilimumab in Patients with Metastatic Melanoma. New England Journal of Medicine, 363(8), 711-723. doi: 10.1056/NEJMoa1003466
Huang, T. (1996) Computer Vision : Evolution And Promise (PDF). 19th CERN School of Computing. Geneva: CERN. pp. 21–25.
Hueglin, C., Gehrig, R., Baltensperger, U., Gysel, M., Monn, C., & Vonmont, H. (2005). Chemical characterisation of PM2.5, PM10 and coarse particles at urban, near-city and rural sites in Switzerland. Atmospheric Environment, 39(4), 637-651. doi: http://dx.doi.org/10.1016/j.atmosenv.2004.10.027
Kampa, M., & Castanas, E. (2008). Human health effects of air pollution. Environmental Pollution, 151(2), 362-367. doi: http://dx.doi.org/10.1016/j.envpol.2007.06.012
Laden, F., Neas, L. M., Dockery, D. W., & Schwartz, J. (2000). Association of fine particulate matter from different sources with daily mortality in six U.S. cities. Environmental Health Perspectives, 108(10), 941-947.
Lienhart, R., & Maydt, J. (2002, 2002). An extended set of Haar-like features for rapid object detection. Paper presented at the Proceedings. International Conference on Image Processing.
Monn, C., Fuchs, A., Högger, D., Junker, M., Kogelschatz, D., Roth, N., & Wanner, H. U. (1997). Particulate matter less than 10 μm (PM10) and fine particles less than 2.5 μm (PM2.5): relationships between indoor, outdoor and personal concentrations. Science of The Total Environment, 208(1), 15-21. doi: http://dx.doi.org/10.1016/S0048-9697(97)00271-4
Nemery, B., Hoet, P. H. M., & Nemmar, A. The Meuse Valley fog of 1930: an air pollution disaster. The Lancet, 357(9257), 704-708. doi: 10.1016/S0140-6736(00)04135-0
Pozzi, R., De Berardis, B., Paoletti, L., & Guastadisegni, C. (2003). Inflammatory mediators induced by coarse (PM2.5–10) and fine (PM2.5) urban air particles in RAW 264.7 cells. Toxicology, 183(1), 243-254. doi: http://dx.doi.org/10.1016/S0300-483X(02)00545-0
Seaton, A., Godden, D., MacNee, W., & Donaldson, K. (1995). Particulate air pollution and acute health effects. The Lancet, 345(8943), 176-178. doi: http://dx.doi.org/10.1016/S0140-6736(95)90173-6
Song, Y., Zhang, Y., Xie, S., Zeng, L., Zheng, M., Salmon, L. G., . . . Slanina, S. (2006). Source apportionment of PM2.5 in Beijing by positive matrix factorization. Atmospheric Environment, 40(8), 1526-1537. doi: http://dx.doi.org/10.1016/j.atmosenv.2005.10.039
24
Soukup, J. M., & Becker, S. (2001). Human Alveolar Macrophage Responses to Air Pollution Particulates Are Associated with Insoluble Components of Coarse Material, Including Particulate Endotoxin. Toxicology and Applied Pharmacology, 171(1), 20-26. doi: http://dx.doi.org/10.1006/taap.2000.9096
Viola, P., & Jones, M. (2001, 2001). Rapid object detection using a boosted cascade of simple features. Paper presented at the Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
Viola, P., & Jones, M. J. (2004). Robust Real-Time Face Detection. International Journal of Computer Vision, 57(2), 137-154. doi: 10.1023/B:VISI.0000013087.49260.fb
劉憲民. (2007). 道路揚塵評估結果與懸浮微粒監測結果之關聯性分析. 臺灣大學. Available from Airiti AiritiLibrary database. (2007年)
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊