Deep Architecture for Citywide Travel Time Estimation Incorporating Contextual Information

Autor:	Kun Tang, Aemal J. Khattak, Shuyan Chen, Yingjiu Pan
Rok vydání:	2019
Předmět:	Estimation 050210 logistics & transportation Computer science business.industry Applied Mathematics Deep learning 05 social sciences Aerospace Engineering 02 engineering and technology Data science Computer Science Applications Data-driven Travel time Control and Systems Engineering 0502 economics and business Automotive Engineering 0202 electrical engineering electronic engineering information engineering Contextual information 020201 artificial intelligence & image processing Artificial intelligence Architecture business Intelligent transportation system Software Information Systems
Zdroj:	Journal of Intelligent Transportation Systems. 25:313-329
ISSN:	1547-2442 1547-2450
DOI:	10.1080/15472450.2019.1617141
Popis:	To meet the growing demand of accurate and reliable travel time information in intelligent transportation systems, this a develops a deep architecture incorporating contextual information to estima...
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::fd60979d01a4e1bbeebefe4615a2f01a https://doi.org/10.1080/15472450.2019.1617141 Zobrazit plný text záznamu