Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | 최락현 | - |
| dc.contributor.author | 강원석 | - |
| dc.contributor.author | 손창식 | - |
| dc.date.accessioned | 2023-12-26T20:43:23Z | - |
| dc.date.available | 2023-12-26T20:43:23Z | - |
| dc.date.created | 2017-12-13 | - |
| dc.date.issued | 2017-11-11 | - |
| dc.identifier.uri | http://hdl.handle.net/20.500.11750/47055 | - |
| dc.description.abstract | Particulate Matter(PM2.5) has various adverse effects on health. Climate and industry activity and traffic volume are the main causes, especially in urban area. In order to construct an effective forecasting system, many measurement systems are required, but it is impossible in reality. Therefore, in this study, we propose a method to infer PM2.5 condition by using rule induction technique. The experimental results showed a classification accuracy of 71%. | - |
| dc.language | Korean | - |
| dc.publisher | 대한임베디드공학회 | - |
| dc.title | 기상 데이터를 이용한 초미세먼지 상태 추론 | - |
| dc.title.alternative | Particulate Matter(PM2.5) state inference using weather data | - |
| dc.type | Conference Paper | - |
| dc.identifier.bibliographicCitation | 2017 대한임베디드공학회 추계학술대회, pp.373 - 376 | - |
| dc.citation.conferencePlace | KO | - |
| dc.citation.conferencePlace | 제주 | - |
| dc.citation.endPage | 376 | - |
| dc.citation.startPage | 373 | - |
| dc.citation.title | 2017 대한임베디드공학회 추계학술대회 | - |
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