A Prediction Model Based on Relevance Vector Machine and Granularity Analysis
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cho, Young Im | - |
dc.date.available | 2020-02-28T00:43:36Z | - |
dc.date.created | 2020-02-07 | - |
dc.date.issued | 2016-09-25 | - |
dc.identifier.issn | 1598-2645 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/7877 | - |
dc.description.abstract | In this paper, a yield prediction model based on relevance vector machine (RVM) and a granular computing model (quotient space theory) is presented. With a granular computing model, massive and complex meteorological data can be analyzed at different layers of different grain sizes, and new meteorological feature data sets can be formed in this way. In order to forecast the crop yield, a grey model is introduced to label the training sample data sets, which also can be used for computing the tendency yield. An RVM algorithm is introduced as the classification model for meteorological data mining. Experiments on data sets from the real world using this model show an advantage in terms of yield prediction compared with other models. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | KOREAN INST INTELLIGENT SYSTEMS | - |
dc.relation.isPartOf | INTERNATIONAL JOURNAL OF FUZZY LOGIC AND INTELLIGENT SYSTEMS | - |
dc.subject | FUZZY-LOGIC | - |
dc.title | A Prediction Model Based on Relevance Vector Machine and Granularity Analysis | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 2 | - |
dc.identifier.wosid | 000413894500002 | - |
dc.identifier.doi | 10.5391/IJFIS.2016.16.3.157 | - |
dc.identifier.bibliographicCitation | INTERNATIONAL JOURNAL OF FUZZY LOGIC AND INTELLIGENT SYSTEMS, v.16, no.3, pp.157 - 162 | - |
dc.identifier.kciid | ART002151961 | - |
dc.citation.endPage | 162 | - |
dc.citation.startPage | 157 | - |
dc.citation.title | INTERNATIONAL JOURNAL OF FUZZY LOGIC AND INTELLIGENT SYSTEMS | - |
dc.citation.volume | 16 | - |
dc.citation.number | 3 | - |
dc.contributor.affiliatedAuthor | Cho, Young Im | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | Quotient space theory | - |
dc.subject.keywordAuthor | Granular computing | - |
dc.subject.keywordAuthor | RVM | - |
dc.subject.keywordAuthor | Grey model | - |
dc.subject.keywordPlus | FUZZY-LOGIC | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.description.journalRegisteredClass | kci | - |
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