{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T13:14:58Z","timestamp":1772802898730,"version":"3.50.1"},"reference-count":29,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,12]]},"DOI":"10.1109\/bigdata.2017.8258162","type":"proceedings-article","created":{"date-parts":[[2018,1,15]],"date-time":"2018-01-15T22:47:28Z","timestamp":1516056448000},"page":"2141-2150","source":"Crossref","is-referenced-by-count":39,"title":["DxNAT \u2014 Deep neural networks for explaining non-recurring traffic congestion"],"prefix":"10.1109","author":[{"given":"Fangzhou","family":"Sun","sequence":"first","affiliation":[]},{"given":"Abhishek","family":"Dubey","sequence":"additional","affiliation":[]},{"given":"Jules","family":"White","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2014.2305334"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-017-0487-4"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"1010","DOI":"10.1145\/2020408.2020571","article-title":"Discovering spatiotemporal causal interactions in traffic data streams","author":"liu","year":"2011","journal-title":"Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.sbspro.2013.08.235"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1002\/atr.1241"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvlc.2014.10.028"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2015.206"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2016.2641903"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/FISTS.2011.5973643"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2012.2186127"},{"key":"ref28","article-title":"Keras: The python deep learning library","year":"2017","journal-title":"Keras"},{"key":"ref4","author":"robinson","year":"2006","journal-title":"The development and application of an urban link travel time model using data derived from inductive loop detectors"},{"key":"ref27","author":"works","year":"2017","journal-title":"Detector Performance Analysis Using ROC Curves"},{"key":"ref3","article-title":"The 21st century operation oriented state dots, nchrp project 20-24","author":"lockwood","year":"2006","journal-title":"Transportation research board American Association of State Highway and Transportation Officials Washington DC"},{"key":"ref6","first-page":"53","article-title":"Towards detection of faulty traffic sensors in real-time","author":"zygouras","year":"2015","journal-title":"MUD ICML"},{"key":"ref29","article-title":"Tensorflow: Large-scale machine learning on heterogeneous distributed systems","author":"abadi","year":"2016"},{"key":"ref5","article-title":"Faulty loop data analysis\/correction and loop fault detection","author":"lu","year":"2008","journal-title":"15th World Congress on Intelligent Transport Systems and ITS America's 2008 Annual Meeting"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/6979.880968"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3063386.3063767"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/0968-090X(93)90022-8"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/.2005.1467180"},{"key":"ref1","author":"schrank","year":"2015","journal-title":"2015 Urban mobility scorecard"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/s17030550"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.3390\/s17040818"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.3141\/1959-10"},{"key":"ref24","article-title":"Nashville fire department","year":"2017","journal-title":"M G of Nashville and D County"},{"key":"ref23","year":"0","journal-title":"Here traffic api"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.143.1.7063747"},{"key":"ref25","author":"wiki","year":"2017","journal-title":"Tmc\/location code list\/location types"}],"event":{"name":"2017 IEEE International Conference on Big Data (Big Data)","location":"Boston, MA","start":{"date-parts":[[2017,12,11]]},"end":{"date-parts":[[2017,12,14]]}},"container-title":["2017 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8241556\/8257893\/08258162.pdf?arnumber=8258162","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T16:07:20Z","timestamp":1660320440000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/8258162\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,12]]},"references-count":29,"URL":"https:\/\/doi.org\/10.1109\/bigdata.2017.8258162","relation":{},"subject":[],"published":{"date-parts":[[2017,12]]}}}