文献
J-GLOBAL ID:202002262188412664
整理番号:20A0378912
より安全な道路に向けて 実時間事故検出と特徴分析のためのXGBoostとSHAPの応用【JST・京大機械翻訳】
Toward safer highways, application of XGBoost and SHAP for real-time accident detection and feature analysis
著者 (5件):
Parsa Amir Bahador
(Department of Civil and Materials Engineering, University of Illinois at Chicago, 842 W Taylor St, 2095 ERF, Chicago, IL 60607, United States)
,
Movahedi Ali
(Department of Civil and Materials Engineering, University of Illinois at Chicago, 842 W Taylor St, 2095 ERF, Chicago, IL 60607, United States)
,
Taghipour Homa
(Department of Civil and Materials Engineering, University of Illinois at Chicago, 842 W Taylor St, 2095 ERF, Chicago, IL 60607, United States)
,
Derrible Sybil
(Department of Civil and Materials Engineering, Institute for Environmental Science and Policy, University of Illinois at Chicago, 842 W Taylor St, 2095 ERF, Chicago, IL 60607, United States)
,
Mohammadian Abolfazl (Kouros)
(Department of Civil and Materials Engineering, University of Illinois at Chicago, 842 W Taylor St, 2095 ERF, Chicago, IL 60607, United States)
資料名:
Accident Analysis & Prevention
(Accident Analysis & Prevention)
巻:
136
ページ:
Null
発行年:
2020年
JST資料番号:
D0828A
ISSN:
0001-4575
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
イギリス (GBR)
言語:
英語 (EN)