{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T21:56:15Z","timestamp":1767650175008},"reference-count":17,"publisher":"IGI Global","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,4,1]]},"abstract":"<p>In order to alleviate urban traffic congestion, it is necessary to obtain roadway network traffic flow parameters to estimate the traffic conditions. Single-detector data may not be sufficient to obtain a comprehensive, effective, accurate and high-quality traffic flow data. Neural networks and regression analysis data fusion methods are employed to expand data sources as well as for improving data quality. The multi-source detector data can provide fundamental support for traffic management. An empirical analysis was conducted using acquisition technology employed by the Beijing urban expressway to estimate traffic flow parameters. The results show that the proposed data fusion method is feasible and provides reliable data sources.<\/p>","DOI":"10.4018\/ijcini.2019040105","type":"journal-article","created":{"date-parts":[[2019,4,4]],"date-time":"2019-04-04T14:05:34Z","timestamp":1554386734000},"page":"63-75","source":"Crossref","is-referenced-by-count":5,"title":["Study on Traffic Multi-Source Data Fusion"],"prefix":"10.4018","volume":"13","author":[{"given":"Suping","family":"Liu","sequence":"first","affiliation":[{"name":"Guangdong University of Science and Technology, Guangdong, China"}]},{"given":"Dongbo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Guangdong Institute of Intelligent Manufacturing, Guangdong, China"}]},{"given":"Jialin","family":"Li","sequence":"additional","affiliation":[{"name":"Science and Technology Gannan Normal University, Jiangxi, China"}]}],"member":"2432","reference":[{"key":"IJCINI.2019040105-0","doi-asserted-by":"publisher","DOI":"10.14778\/1920841.1920881"},{"key":"IJCINI.2019040105-1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611973082.27"},{"key":"IJCINI.2019040105-2","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2012.07.003"},{"key":"IJCINI.2019040105-3","doi-asserted-by":"crossref","unstructured":"Honghui, D., Mingchao, W., Maojing, J., Pengfei, Z., Yu, Z., Limin, J., & Yong, Q. (2013, May). A fusion model for multi-source detect data of section average velocity based on BP network. In 2013 25th Chinese Control and Decision Conference (CCDC) (pp. 2198-2203). IEEE.","DOI":"10.1109\/CCDC.2013.6561300"},{"key":"IJCINI.2019040105-4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-19853-3_65"},{"key":"IJCINI.2019040105-5","doi-asserted-by":"publisher","DOI":"10.1061\/9780784413364.056"},{"key":"IJCINI.2019040105-6","doi-asserted-by":"publisher","DOI":"10.1006\/jagm.1999.1048"},{"key":"IJCINI.2019040105-7","unstructured":"Gao, M. X., & He, G.-G. (2011). An arc labeling algorithm for shortest path problem considering turn penalties and prohibitions at intersections. Journal of Lanzhou Jiaotong University."},{"key":"IJCINI.2019040105-8","doi-asserted-by":"publisher","DOI":"10.1006\/jagm.1998.0968"},{"key":"IJCINI.2019040105-9","doi-asserted-by":"publisher","DOI":"10.2174\/1874110X01509010306"},{"issue":"1","key":"IJCINI.2019040105-10","first-page":"66","article-title":"Solving traveling salesman problem with characteristic of clustering by parallel genetic algorithm.","volume":"35","author":"X.Hu","year":"2004","journal-title":"Computer Engineering and Application"},{"key":"IJCINI.2019040105-11","doi-asserted-by":"publisher","DOI":"10.1016\/S0968-090X(97)00018-1"},{"key":"IJCINI.2019040105-12","doi-asserted-by":"publisher","DOI":"10.1016\/j.forsciint.2015.12.031"},{"key":"IJCINI.2019040105-13","doi-asserted-by":"publisher","DOI":"10.3141\/1804-23"},{"key":"IJCINI.2019040105-14","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-3614-9_55"},{"key":"IJCINI.2019040105-15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-37835-5_33"},{"key":"IJCINI.2019040105-16","first-page":"978","article-title":"Acquisition of traffic flow density using multi-source data fusion.","author":"T.Zhu","year":"2012","journal-title":"Proceeding of International Conference on Measurement, Information and Control (MIC)"}],"container-title":["International Journal of Cognitive Informatics and Natural Intelligence"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=226940","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,7]],"date-time":"2022-05-07T01:46:25Z","timestamp":1651887985000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJCINI.2019040105"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2019,4,1]]},"references-count":17,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2019,4]]}},"URL":"https:\/\/doi.org\/10.4018\/ijcini.2019040105","relation":{},"ISSN":["1557-3958","1557-3966"],"issn-type":[{"value":"1557-3958","type":"print"},{"value":"1557-3966","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,1]]}}}