Cited 0 time in
신경회로망을 사용한 포화 및 과열 증기표의 동시 모델링
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | 이태환 | - |
| dc.contributor.author | 박진현 | - |
| dc.date.accessioned | 2022-12-26T23:20:22Z | - |
| dc.date.available | 2022-12-26T23:20:22Z | - |
| dc.date.issued | 2014 | - |
| dc.identifier.issn | 1229-604X | - |
| dc.identifier.issn | 2508-3805 | - |
| dc.identifier.uri | https://scholarworks.gnu.ac.kr/handle/sw.gnu/19255 | - |
| dc.description.abstract | The steam table in saturated and superheated region was modeled simultaneously using the neuralnetworks. A variable was introduced to distinguish between the saturation and the superheat. The relativeerrors were compared with the quadratic spline interpolation method. The relative errors by the neural networks were superior to those by the quadratic splineinterpolation method over almost all ranges of temperatures and properties. The overall errors in thesaturated region were better than those in the superheated region. From the analysis, it was confirmed that the neural networks could be a very powerful tool forsimultaneous modeling of superheated and saturated steam table. | - |
| dc.format.extent | 6 | - |
| dc.language | 한국어 | - |
| dc.language.iso | KOR | - |
| dc.publisher | 한국기계기술학회 | - |
| dc.title | 신경회로망을 사용한 포화 및 과열 증기표의 동시 모델링 | - |
| dc.title.alternative | A simultaneous modeling of saturated and superheated steam table using the neural networks | - |
| dc.type | Article | - |
| dc.publisher.location | 대한민국 | - |
| dc.identifier.doi | 10.17958/ksmt.16.6.201412.2035 | - |
| dc.identifier.bibliographicCitation | 한국기계기술학회지, v.16, no.6, pp 2035 - 2040 | - |
| dc.citation.title | 한국기계기술학회지 | - |
| dc.citation.volume | 16 | - |
| dc.citation.number | 6 | - |
| dc.citation.startPage | 2035 | - |
| dc.citation.endPage | 2040 | - |
| dc.identifier.kciid | ART001936909 | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | kci | - |
| dc.subject.keywordAuthor | Steam table(증기표) | - |
| dc.subject.keywordAuthor | Saturated state(포화 상태) | - |
| dc.subject.keywordAuthor | Superheated state(과열 상태) | - |
| dc.subject.keywordAuthor | Neural networks(신경회로망) | - |
| dc.subject.keywordAuthor | Spline interpolation method(스플라인 보간법) | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
Gyeongsang National University Central Library, 501, Jinju-daero, Jinju-si, Gyeongsangnam-do, 52828, Republic of Korea+82-55-772-0532
COPYRIGHT 2022 GYEONGSANG NATIONAL UNIVERSITY LIBRARY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.
