2011-06-092024-05-17https://scholars.lib.ntu.edu.tw/handle/123456789/684825摘要：氣候變遷的相關議題在近年來已成為眾所矚目的焦點，經由前人的研究發現，與動 植物生存及成長息息相關的空氣品質問題，亦會受到氣候變遷的影響而有所變化。 評估空氣品質的指標有許多種，臭氧濃度是其中一個重點評估項目，其對人體健康 及作物的成長均有影響。於臺灣地區的空氣監測結果中，亦可發現臭氧是臺灣目前 主要的空氣污染物之一，尤其在人口越密集的地區，臭氧濃度有越高的趨勢。本計 畫擬收集氣象因子與臭氧濃度資料，分析氣象因子與臭氧濃度的關係，並選擇合適 的類神經網路，利用類神經網路能處理高度非線性問題、架構簡單且迅速的優勢 ，連結氣象因子與臭氧濃度之間的複雜關係，藉此探討在大環境的氣候變遷影響下 ，臭氧濃度未來的變化潛勢。此成果將可作為未來空氣品質的重要參考，期望能有 助於相關單位制定政策或方向，以減少空氣污染對人民健康及農作物成長可能造成 的負面影響。<br> Abstract: Topics related to climate changes attracted wide public attention in recent years. Previous researches show that the air quality is also affected by the climate change. Many indexes are used to evaluate the air quality. Ozone, which has an influence on the human health and plant growth, is one of the indexes. Ozone is one of the major air pollutants in Taiwan, especially in highly populated area. In this project, data of meteorological factors and ozone concentration will be collected and their relationship will be investigated. Appropriate neural networks will be constructed to connect the complicated relation between meteorological factors and ozone concentration. Change in ozone air pollution associated with global climate change will be investigated using the proposed ANN model.氣候變遷臭氧類神經網路Climate ChangeOzoneANN