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Robustness Analysis of Air Route Network Based on Topology Potential and Relative Entropy Methods
Air route network (ARN) is the important carrier of air transport, and its robustness has important influence on the safety and stability of air transport. To analyze the robustness of ARN, in this paper, a topology potential relative entropy (TPRE) model is proposed, based on topology potential (TP...
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Published in: | Journal of advanced transportation 2021, Vol.2021, p.1-11 |
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description | Air route network (ARN) is the important carrier of air transport, and its robustness has important influence on the safety and stability of air transport. To analyze the robustness of ARN, in this paper, a topology potential relative entropy (TPRE) model is proposed, based on topology potential (TP) and relative entropy (RE) methods. Firstly, the TPRE model is established as the theoretical basis for the research. Secondly, an air route reduction network (ARRN) model is constructed according to real Chinese ARN. Besides, the basic topology features of ARRN are given by complex network theory. To prove the applicability, objectivity, and accuracy of the proposed method, attack strategies including random, degree, betweenness, closeness, eigenvector, and Bonacich are used to attack ARRN. Eventually, the performance of ARRN robustness is analyzed by network efficiency, size of giant component, and the proposed TPRE model. This conclusion has practical significance for optimizing ARN structure and improving airspace efficiency. |
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To analyze the robustness of ARN, in this paper, a topology potential relative entropy (TPRE) model is proposed, based on topology potential (TP) and relative entropy (RE) methods. Firstly, the TPRE model is established as the theoretical basis for the research. Secondly, an air route reduction network (ARRN) model is constructed according to real Chinese ARN. Besides, the basic topology features of ARRN are given by complex network theory. To prove the applicability, objectivity, and accuracy of the proposed method, attack strategies including random, degree, betweenness, closeness, eigenvector, and Bonacich are used to attack ARRN. Eventually, the performance of ARRN robustness is analyzed by network efficiency, size of giant component, and the proposed TPRE model. This conclusion has practical significance for optimizing ARN structure and improving airspace efficiency.</description><identifier>ISSN: 0197-6729</identifier><identifier>EISSN: 2042-3195</identifier><identifier>DOI: 10.1155/2021/5527423</identifier><language>eng</language><publisher>London: Hindawi</publisher><subject>Air transportation ; Air transportation industry ; Aircraft ; Aircraft accidents & safety ; Airlines ; Airports ; Alliances ; Connectivity ; Eigenvectors ; Entropy ; Literature reviews ; Robustness ; Stability analysis ; Topology</subject><ispartof>Journal of advanced transportation, 2021, Vol.2021, p.1-11</ispartof><rights>Copyright © 2021 Guangjian Ren.</rights><rights>COPYRIGHT 2021 John Wiley & Sons, Inc.</rights><rights>Copyright © 2021 Guangjian Ren. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c631t-2dcd8cdb9d32dd1280fdb1a4dad98e6c5f081d446d1b585a9f1ce7a55b39e743</citedby><cites>FETCH-LOGICAL-c631t-2dcd8cdb9d32dd1280fdb1a4dad98e6c5f081d446d1b585a9f1ce7a55b39e743</cites><orcidid>0000-0003-2235-7484</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2554893961/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2554893961?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,4024,11688,25753,27923,27924,27925,36060,37012,44363,44590,74895,75126</link.rule.ids></links><search><contributor>De Barros, Alexandre</contributor><contributor>Alexandre De Barros</contributor><creatorcontrib>Ren, Guangjian</creatorcontrib><title>Robustness Analysis of Air Route Network Based on Topology Potential and Relative Entropy Methods</title><title>Journal of advanced transportation</title><description>Air route network (ARN) is the important carrier of air transport, and its robustness has important influence on the safety and stability of air transport. 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To analyze the robustness of ARN, in this paper, a topology potential relative entropy (TPRE) model is proposed, based on topology potential (TP) and relative entropy (RE) methods. Firstly, the TPRE model is established as the theoretical basis for the research. Secondly, an air route reduction network (ARRN) model is constructed according to real Chinese ARN. Besides, the basic topology features of ARRN are given by complex network theory. To prove the applicability, objectivity, and accuracy of the proposed method, attack strategies including random, degree, betweenness, closeness, eigenvector, and Bonacich are used to attack ARRN. Eventually, the performance of ARRN robustness is analyzed by network efficiency, size of giant component, and the proposed TPRE model. This conclusion has practical significance for optimizing ARN structure and improving airspace efficiency.</abstract><cop>London</cop><pub>Hindawi</pub><doi>10.1155/2021/5527423</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0003-2235-7484</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Air transportation Air transportation industry Aircraft Aircraft accidents & safety Airlines Airports Alliances Connectivity Eigenvectors Entropy Literature reviews Robustness Stability analysis Topology |
title | Robustness Analysis of Air Route Network Based on Topology Potential and Relative Entropy Methods |
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