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기계학습기반 양돈생산성 예측방안

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dc.contributor.author이웅섭-
dc.contributor.author성길영-
dc.contributor.author반태원-
dc.contributor.author함영화-
dc.date.accessioned2022-12-26T14:01:05Z-
dc.date.available2022-12-26T14:01:05Z-
dc.date.issued2020-
dc.identifier.issn2234-4772-
dc.identifier.issn2288-4165-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/8023-
dc.description.abstractSmart pig farm which is based on IoT has been widely adopted by many pig farmers. In order to achieve optimal control of smart pig farm, the relation between environmental conditions and performance metric should be characterized. In this study, the relation between multiple environmental conditions including temperature, humidity and various performance metrics, which are daily gain, feed intake, and MSY, is analyzed based on data obtained from 55 real pig farm. Especially, based on preprocessing of data, various regression based machine learning algorithms are considered. Through performance evaluation, we show that the performance can be predicted with high precision, which can improve the efficiency of management.-
dc.format.extent4-
dc.language한국어-
dc.language.isoKOR-
dc.publisher한국정보통신학회-
dc.title기계학습기반 양돈생산성 예측방안-
dc.title.alternativeProduction Performance Prediction of Pig Farming using Machine Learning-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.doi10.6109/jkiice.2020.24.1.130-
dc.identifier.bibliographicCitation한국정보통신학회논문지, v.24, no.1, pp 130 - 133-
dc.citation.title한국정보통신학회논문지-
dc.citation.volume24-
dc.citation.number1-
dc.citation.startPage130-
dc.citation.endPage133-
dc.identifier.kciidART002555024-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthorMachine learning-
dc.subject.keywordAuthorpig farm-
dc.subject.keywordAuthorbig data-
dc.subject.keywordAuthorperformance metric-
dc.subject.keywordAuthorsmart farm-
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해양과학대학 > 지능형통신공학과 > Journal Articles

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