{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T07:34:06Z","timestamp":1778657646313,"version":"3.51.4"},"reference-count":16,"publisher":"Wiley","license":[{"start":{"date-parts":[[2019,4,9]],"date-time":"2019-04-09T00:00:00Z","timestamp":1554768000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Liaoning Province Doctoral","award":["20170520141"],"award-info":[{"award-number":["20170520141"]}]},{"name":"Liaoning Province Doctoral","award":["20170003"],"award-info":[{"award-number":["20170003"]}]},{"name":"Liaoning Provincial Natural Science Fund","award":["20170520141"],"award-info":[{"award-number":["20170520141"]}]},{"name":"Liaoning Provincial Natural Science Fund","award":["20170003"],"award-info":[{"award-number":["20170003"]}]},{"name":"Liaoning Provincial Public Welfare Research Fund","award":["20170520141"],"award-info":[{"award-number":["20170520141"]}]},{"name":"Liaoning Provincial Public Welfare Research Fund","award":["20170003"],"award-info":[{"award-number":["20170003"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Sensors"],"published-print":{"date-parts":[[2019,4,9]]},"abstract":"<jats:p>Rural traffic network (RTN), as a complex network, plays a significant role in the field of resisting natural disasters and emergencies. In this paper, we analyze the vulnerability of RTN via three traffic network models (i.e., No-power Traffic Network Model (NTNM), Distance Weight Traffic Network Model (DWTNM), and Road Level Weight Traffic Network Model (RLWTNM)). Firstly, based on the complex network theory, RTN is constructed by using road mapping method, according to the topological features. Secondly, Random Attack (RA) and Deliberate Attack (DA) strategies are used to analyze network vulnerability in three rural traffic network models. By analyzing the attack tolerance of RTN under the condition of different attack patterns, we find that the road level weight traffic network has a good performance to represent the vulnerability of RTN.<\/jats:p>","DOI":"10.1155\/2019\/6530469","type":"journal-article","created":{"date-parts":[[2019,4,9]],"date-time":"2019-04-09T23:43:00Z","timestamp":1554853380000},"page":"1-9","source":"Crossref","is-referenced-by-count":7,"title":["Topological Characteristics and Vulnerability Analysis of Rural Traffic Network"],"prefix":"10.1155","volume":"2019","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7777-3050","authenticated-orcid":true,"given":"Xia","family":"Zhu","sequence":"first","affiliation":[{"name":"Cartography and Geographic Information Engineering, Liaoning Technical University, Fuxin 12300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weidong","family":"Song","sequence":"additional","affiliation":[{"name":"Cartography and Geographic Information Engineering, Liaoning Technical University, Fuxin 12300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lin","family":"Gao","sequence":"additional","affiliation":[{"name":"Cartography and Geographic Information Engineering, Liaoning Technical University, Fuxin 12300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1140\/epjb\/e2003-00095-5"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1539-6924.2006.00791.x"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1007\/s11116-011-9350-0"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1142\/S021798490400758X"},{"issue":"2","key":"5","doi-asserted-by":"crossref","first-page":"35","DOI":"10.5963\/IJCSAI0402002","volume":"4","year":"2014","journal-title":"International Journal of Computer Science & Artificial Intelligence"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1038\/451893a"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1038\/nature08932"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0069829"},{"key":"9","doi-asserted-by":"crossref","first-page":"5638","DOI":"10.1038\/srep05638","volume":"4","year":"2014","journal-title":"Scientific Reports"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2016.2566801"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1007\/s40844-015-0025-y"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1080\/10286608.2016.1148142"},{"issue":"03","key":"13","first-page":"101","year":"2017","journal-title":"Journal of Highway and Transportation"},{"key":"14","year":"2012"},{"issue":"3","key":"15","first-page":"10","volume":"27","year":"2009","journal-title":"Systems Engineering"},{"key":"16","year":"2012"}],"container-title":["Journal of Sensors"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/js\/2019\/6530469.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/js\/2019\/6530469.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/js\/2019\/6530469.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,15]],"date-time":"2023-09-15T15:21:34Z","timestamp":1694791294000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/js\/2019\/6530469\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,9]]},"references-count":16,"alternative-id":["6530469","6530469"],"URL":"https:\/\/doi.org\/10.1155\/2019\/6530469","relation":{},"ISSN":["1687-725X","1687-7268"],"issn-type":[{"value":"1687-725X","type":"print"},{"value":"1687-7268","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,9]]}}}