ÇѱÛÁ¦¸ñ(Korean Title) |
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¿µ¹®Á¦¸ñ(English Title) |
Particulate Matter Prediction Model using Artificial Neural Network |
ÀúÀÚ(Author) |
Á¤¿ëÁø
Á¶°æ¿ì
°Ã¶±Ô
¿ÀâÇå
Yong-jin Jung
Kyoung-woo Cho
Chul-gyu Kang
Chang-heon Oh
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¿ø¹®¼ö·Ïó(Citation) |
VOL 22 NO. 02 PP. 0623 ~ 0625 (2018. 10) |
Çѱ۳»¿ë (Korean Abstract) |
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¿µ¹®³»¿ë (English Abstract) |
As the issue of particulate matter spreads, services for providing particulate matter information in real time are increasing. However, when a sensor node for collecting particulate matter is defective, a corresponding service may not be provided. To solve these problems, it is necessary to predict and deduce particulate matter. In this paper, a particulate matter prediction model is designed using artificial neural network algorithm based on past particulate matter and meteorological data to predict particulate matter. Also, the prediction results are compared by learning the input data of the model in the design stage.
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Å°¿öµå(Keyword) |
Particulate matter
Deep learning
Artificial neural network
Prediction model
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