인공신경망을 활용한 비위생 매립장 폐기물 특성 평가
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김진환 | - |
dc.contributor.author | 조진우 | - |
dc.contributor.author | 신휴성 | - |
dc.contributor.author | 박재우 | - |
dc.date.accessioned | 2022-07-16T02:59:02Z | - |
dc.date.available | 2022-07-16T02:59:02Z | - |
dc.date.created | 2021-05-13 | - |
dc.date.issued | 2014-09 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/159095 | - |
dc.description.abstract | It is necessary to understand landfill status and waste characteristics for utilization of ended unsanitary landfill sites. In this study, we applied the artificial neural network(ANN) to derive the relationship between general characteristics of unsanitary landfills and results of leachate analysis. The study area is unsanitary landfills ended in the late 1980s, landfill site data and leachate analysis data were learned by the ANN. Results from the ANN, we were able to predict the amount of ammonium from unsanitary landfill site characteristics. We need more ANN models and analysis to predict accurately leachate composition. | - |
dc.language | 한국어 | - |
dc.language.iso | ko | - |
dc.publisher | 한국지반환경공학회 | - |
dc.title | 인공신경망을 활용한 비위생 매립장 폐기물 특성 평가 | - |
dc.title.alternative | Evaluation of Unsanitary Landfill Waste Characteristics using the Artificial Neural Network | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | 박재우 | - |
dc.identifier.bibliographicCitation | 2014년 한국지반환경공학회 학술발표회논문집, pp.256 - 259 | - |
dc.relation.isPartOf | 2014년 한국지반환경공학회 학술발표회논문집 | - |
dc.citation.title | 2014년 한국지반환경공학회 학술발표회논문집 | - |
dc.citation.startPage | 256 | - |
dc.citation.endPage | 259 | - |
dc.type.rims | ART | - |
dc.type.docType | 정기학술지(Article(Perspective Article포함)) | - |
dc.description.journalClass | 3 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | other | - |
dc.subject.keywordAuthor | Unsanitary landfill | - |
dc.subject.keywordAuthor | Artificial neural network | - |
dc.subject.keywordAuthor | Waste characteristics | - |
dc.identifier.url | https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE02479141 | - |
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