標題: Fuzzy neural incident detection algorithms with rolling training procedure
作者: Lan, LW
Huang, YC
運輸與物流管理系 註:原交通所+運管所
Department of Transportation and Logistics Management
關鍵字: freeway incident detection algorithm;fuzzy neural network;rolling training procedure;traffic simulation
公開日期: 2003
摘要: This paper attempts to establish a fuzzy neural automatic incident detection (FNAID) algorithm, using back-propagation training procedures. A rolling training procedure continuously updating the traffic flow parameters is proposed to enhance the adaptability of FNAID to different traffic flow conditions. A real incident case is deliberately generated to calibrate the traffic simulator-Paramics. To validate the FNAID with and without rolling training procedure, the calibrated Paramics is used to simulate sufficient incident samples. The off-line tests and statistic tests conclude that under various traffic flow conditions, the FNAID with rolling training procedure has better detection performance than the one without rolling.
URI: http://hdl.handle.net/11536/18483
ISSN: 1348-5393
期刊: PROCEEDINGS OF THE EASTERN ASIA SOCIETY FOR TRANSPORTATION STUDIES, Vol 4, Nos 1 AND 2
Volume: 4
Issue: 1-2
起始頁: 1200
結束頁: 1212
Appears in Collections:Conferences Paper