文献
J-GLOBAL ID:201702228450471478
整理番号:17A0398487
交通衝突頻度モデル化のための最適化されたニューラルネットワークからのルール抽出【Powered by NICT】
Rule extraction from an optimized neural network for traffic crash frequency modeling
著者 (6件):
Zeng Qiang
(School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, Guangdong 510641, PR China)
,
Zeng Qiang
(Urban Transport Research Center, School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan 410075, PR China)
,
Huang Helai
(Urban Transport Research Center, School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan 410075, PR China)
,
Pei Xin
(Department of Automation, Tsinghua University, Beijing, PR China)
,
Wong S.C.
(Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong)
,
Gao Mingyun
(Business School of Hunan University, Changsha, Hunan 410082, PR China)
資料名:
Accident Analysis & Prevention
(Accident Analysis & Prevention)
巻:
97
ページ:
87-95
発行年:
2016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)