Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

머신러닝을 이용한 교통사고 사상자 수 예측 : 서울시 공공데이터를 대상으로

Full metadata record
DC Field Value Language
dc.contributor.authorLEE, Hong Chul-
dc.date.accessioned2022-04-02T10:42:24Z-
dc.date.available2022-04-02T10:42:24Z-
dc.date.created2022-04-02-
dc.date.issued2021-01-22-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/139514-
dc.publisher한국컴퓨터정보학회-
dc.subject머신러닝, 교통사고, 사상자수 예측, DecisionTree, RandomForest, LightGBM, XGBoost-
dc.title머신러닝을 이용한 교통사고 사상자 수 예측 : 서울시 공공데이터를 대상으로-
dc.title.alternativePrediction Of Traffic Accident Casualties Using Machine Learning : For Seoul Public Data-
dc.typeConference-
dc.contributor.affiliatedAuthorLEE, Hong Chul-
dc.identifier.bibliographicCitation2021년 한국컴퓨터정보학회 동계학술대회-
dc.relation.isPartOf2021년 한국컴퓨터정보학회 동계학술대회-
dc.relation.isPartOf한국컴퓨터정보학회 학술발표논문집-
dc.citation.title2021년 한국컴퓨터정보학회 동계학술대회-
dc.citation.conferencePlaceKO-
dc.citation.conferenceDate2021-01-21-
dc.type.rimsCONF-
dc.description.journalClass2-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Engineering > School of Industrial and Management Engineering > 2. Conference Papers

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher LEE, Hong Chul photo

LEE, Hong Chul
공과대학 (산업경영공학부)
Read more

Altmetrics

Total Views & Downloads

BROWSE