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Predicting the impact of hydraulic retention time and biodegradability on the performance of sludge acidogenesis using an artificial neural network
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kumar Pandey, Ashutosh | - |
| dc.contributor.author | Park, Jungsu | - |
| dc.contributor.author | Muhorakeye, Alice | - |
| dc.contributor.author | Morya, Raj | - |
| dc.contributor.author | Kim, Sang-Hyoun | - |
| dc.date.accessioned | 2023-04-12T02:40:03Z | - |
| dc.date.available | 2023-04-12T02:40:03Z | - |
| dc.date.issued | 2023-03 | - |
| dc.identifier.issn | 0960-8524 | - |
| dc.identifier.issn | 1873-2976 | - |
| dc.identifier.uri | https://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/6441 | - |
| dc.publisher | Elsevier BV | - |
| dc.title | Predicting the impact of hydraulic retention time and biodegradability on the performance of sludge acidogenesis using an artificial neural network | - |
| dc.type | Article | - |
| dc.publisher.location | 영국 | - |
| dc.identifier.doi | 10.1016/j.biortech.2023.128629 | - |
| dc.identifier.scopusid | 2-s2.0-85146563292 | - |
| dc.identifier.bibliographicCitation | Bioresource Technology, v.372, pp 128629 | - |
| dc.citation.title | Bioresource Technology | - |
| dc.citation.volume | 372 | - |
| dc.citation.startPage | 128629 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
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Collections - College of Engineering > 공과대학 사회환경시스템공학부 > 공과대학 건설환경공학과 > 1. Journal Articles
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