DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, BS | ko |
dc.contributor.author | Kim, Tag-Gon | ko |
dc.date.accessioned | 2019-12-23T07:20:14Z | - |
dc.date.available | 2019-12-23T07:20:14Z | - |
dc.date.created | 2019-12-23 | - |
dc.date.created | 2019-12-23 | - |
dc.date.created | 2019-12-23 | - |
dc.date.issued | 2019-12 | - |
dc.identifier.citation | INTERNATIONAL JOURNAL OF SIMULATION MODELLING, v.18, no.4, pp.608 - 619 | - |
dc.identifier.issn | 1726-4529 | - |
dc.identifier.uri | http://hdl.handle.net/10203/270279 | - |
dc.description.abstract | Modelling and simulation (M&S) is one of the fundamental methods of performance analysis. In other words, how well a modeller builds a model is a key point of a successful performance analysis. Before such a performance analysis, a model for prediction should be constructed. There are two types of models: data model and simulation model. Data model represents correlational relationships between one set of data and another. Conversely, simulation model represents causal relationships between a set of controlled inputs and corresponding outputs. This paper identifies the characteristics of each modelling method and presents a cooperative model development process for performance analysis of complex systems. The cooperative method contains conceptual modelling, model classification, and model integration/implementation. The model classification method effectively reflects and maximizes the features compared earlier. Then, they are modelled respectively and integrated. This paper also applies the proposed modelling to develop a model of Hadoop using artificial neural network (ANN) and discrete event systems specification (DEVS). To demonstrate the validity of the case study, it presents experiments to show the possibility of a proposed approach. | - |
dc.language | English | - |
dc.publisher | DAAAM INTERNATIONAL VIENNA | - |
dc.title | COOPERATION OF SIMULATION AND DATA MODEL FOR PERFORMANCE ANALYSIS OF COMPLEX SYSTEMS | - |
dc.type | Article | - |
dc.identifier.wosid | 000500961000005 | - |
dc.identifier.scopusid | 2-s2.0-85077596767 | - |
dc.type.rims | ART | - |
dc.citation.volume | 18 | - |
dc.citation.issue | 4 | - |
dc.citation.beginningpage | 608 | - |
dc.citation.endingpage | 619 | - |
dc.citation.publicationname | INTERNATIONAL JOURNAL OF SIMULATION MODELLING | - |
dc.identifier.doi | 10.2507/IJSIMM18(4)491 | - |
dc.contributor.localauthor | Kim, Tag-Gon | - |
dc.contributor.nonIdAuthor | Kim, BS | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Cooperative Model Development | - |
dc.subject.keywordAuthor | Data Modelling | - |
dc.subject.keywordAuthor | Simulation Modelling | - |
dc.subject.keywordAuthor | Artificial Neural Network | - |
dc.subject.keywordAuthor | Discrete Event Systems Specification (DEVS) | - |
dc.subject.keywordAuthor | Hadoop | - |
dc.subject.keywordPlus | BIG DATA | - |
dc.subject.keywordPlus | CELLULAR-AUTOMATA | - |
dc.subject.keywordPlus | NEURAL-NETWORKS | - |
dc.subject.keywordPlus | MAPREDUCE | - |
dc.subject.keywordPlus | DESIGN | - |
dc.subject.keywordPlus | SPEED | - |
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