자동 회귀 통합 이동 평균 모델 적용을 통한 한국의 자동차 사고에 대한 시계열 예측
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 신현경 | - |
dc.date.available | 2020-03-03T11:46:32Z | - |
dc.date.created | 2020-02-24 | - |
dc.date.issued | 2019-12 | - |
dc.identifier.issn | 2586-4440 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/19300 | - |
dc.description.abstract | Recently, IITS (intelligent integrated transportation system) has been important topic in Smart City related industry. As a main objective of IITS, prevention of traffic jam (due to car accidents) has been attempted with help of advanced sensor and communication technologies. Studies show that car accident has certain correlation with some factors including characteristics of location, weather, driver’s behavior, and time of day. We concentrate our study on observing auto correlativity of car accidents in terms of time of day. In this paper, we performed the ARIMA tests including ADF (augmented Dickey-Fuller) to check the three factors determining auto-regressive, stationarity, and lag order. Summary on forecasting of hourly car crash counts is presented, we show that the traffic accident data obtained in Korea can be applied to ARIMA model and present a result that traffic accidents in Korea have property of being recurrent daily basis. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | 중소기업융합학회 | - |
dc.relation.isPartOf | 융합정보논문지 | - |
dc.title | 자동 회귀 통합 이동 평균 모델 적용을 통한 한국의 자동차 사고에 대한 시계열 예측 | - |
dc.title.alternative | Time Series Forecasting on Car Accidents in Korea Using Auto-Regressive Integrated Moving Average Model | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 2 | - |
dc.identifier.doi | 10.22156/CS4SMB.2019.9.12.054 | - |
dc.identifier.bibliographicCitation | 융합정보논문지, v.9, no.12, pp.54 - 61 | - |
dc.identifier.kciid | ART002534131 | - |
dc.description.isOpenAccess | N | - |
dc.citation.endPage | 61 | - |
dc.citation.startPage | 54 | - |
dc.citation.title | 융합정보논문지 | - |
dc.citation.volume | 9 | - |
dc.citation.number | 12 | - |
dc.contributor.affiliatedAuthor | 신현경 | - |
dc.subject.keywordAuthor | 시계열 분석 | - |
dc.subject.keywordAuthor | 확률 론적 고정 시계열 | - |
dc.subject.keywordAuthor | ARIMA 모델 | - |
dc.subject.keywordAuthor | ADF (Augmented Dickey-Fuller) 테스트 | - |
dc.subject.keywordAuthor | 예측 | - |
dc.subject.keywordAuthor | 자동차 사고 데이터 | - |
dc.subject.keywordAuthor | Time series analysis | - |
dc.subject.keywordAuthor | stochastic stationary time series | - |
dc.subject.keywordAuthor | ARIMA model | - |
dc.subject.keywordAuthor | Augmented Dickey-Fuller (ADF) test | - |
dc.subject.keywordAuthor | Forecasting | - |
dc.subject.keywordAuthor | Car accident data | - |
dc.description.journalRegisteredClass | kci | - |
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