Research of Command Automation System Survivability Assessment Model
Based on the structural complexity of command automation system, starting from command automation system itself and the relationship between system and its environment, survivability analysis of command automation system is divided into three sub-problems of system services, external environment and...
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| creator | Rulin Hu Xinhua He Shaomin Yang |
| description | Based on the structural complexity of command automation system, starting from command automation system itself and the relationship between system and its environment, survivability analysis of command automation system is divided into three sub-problems of system services, external environment and model construction to be analyzed respectively. Therefore, it simplifies the complexity of the problem. Based on the uncertainty of survivability assessment information of command automation system, Bayesian network is introduced into model construction. This paper demonstrates the model construction process of command automation system survivability assessment by an example. This method has a good operability. It can not only quantitatively calculate the survivability probability of command automation system, but can also identify the major environmental factors affecting the system and the weak links of the system by diagnostic reasoning. |
| doi_str_mv | 10.1109/ICINIS.2010.122 |
| format | Conference Proceeding |
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Therefore, it simplifies the complexity of the problem. Based on the uncertainty of survivability assessment information of command automation system, Bayesian network is introduced into model construction. This paper demonstrates the model construction process of command automation system survivability assessment by an example. This method has a good operability. It can not only quantitatively calculate the survivability probability of command automation system, but can also identify the major environmental factors affecting the system and the weak links of the system by diagnostic reasoning.</description><identifier>ISBN: 9781424485482</identifier><identifier>ISBN: 1424485487</identifier><identifier>EISBN: 9780769542492</identifier><identifier>EISBN: 0769542492</identifier><identifier>DOI: 10.1109/ICINIS.2010.122</identifier><language>eng</language><publisher>IEEE</publisher><subject>Analytical models ; Approximation algorithms ; Automation ; Bayesian methods ; bayesian networks ; Cognition ; command automation system ; Inference algorithms ; Mathematical model ; quantitative assessment ; survivability ; uncertainty reasoning</subject><ispartof>2010 Third International Conference on Intelligent Networks and Intelligent Systems, 2010, p.676-679</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5693795$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2057,27924,54919</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5693795$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Rulin Hu</creatorcontrib><creatorcontrib>Xinhua He</creatorcontrib><creatorcontrib>Shaomin Yang</creatorcontrib><title>Research of Command Automation System Survivability Assessment Model</title><title>2010 Third International Conference on Intelligent Networks and Intelligent Systems</title><addtitle>icinis</addtitle><description>Based on the structural complexity of command automation system, starting from command automation system itself and the relationship between system and its environment, survivability analysis of command automation system is divided into three sub-problems of system services, external environment and model construction to be analyzed respectively. Therefore, it simplifies the complexity of the problem. Based on the uncertainty of survivability assessment information of command automation system, Bayesian network is introduced into model construction. This paper demonstrates the model construction process of command automation system survivability assessment by an example. This method has a good operability. It can not only quantitatively calculate the survivability probability of command automation system, but can also identify the major environmental factors affecting the system and the weak links of the system by diagnostic reasoning.</description><subject>Analytical models</subject><subject>Approximation algorithms</subject><subject>Automation</subject><subject>Bayesian methods</subject><subject>bayesian networks</subject><subject>Cognition</subject><subject>command automation system</subject><subject>Inference algorithms</subject><subject>Mathematical model</subject><subject>quantitative assessment</subject><subject>survivability</subject><subject>uncertainty reasoning</subject><isbn>9781424485482</isbn><isbn>1424485487</isbn><isbn>9780769542492</isbn><isbn>0769542492</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjMtKxDAARSMiKGPXLtzkBzrm_ViW-iqMCtb9kKQJBppWmsxA_15HXd17LocLwA1GW4yRvuva7rXrtwSdBkLOQKWlQlJozgjT5PyX8U9nijNFLkGVc7SICClOzhW4f_fZm8V9wjnAdk7JTANsDmVOpsR5gv2ai0-wPyzHeDQ2jrGssMnZ55z8VODLPPjxGlwEM2Zf_ecG9I8PH-1zvXt76tpmV0eNSi0HISkTwkmlsVNWeOICk2EYqOVOeqwcIoawQCl1FFvLgguScks4GxSiG3D79xq99_uvJSazrHsuNJWa029l9Ux_</recordid><startdate>201011</startdate><enddate>201011</enddate><creator>Rulin Hu</creator><creator>Xinhua He</creator><creator>Shaomin Yang</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201011</creationdate><title>Research of Command Automation System Survivability Assessment Model</title><author>Rulin Hu ; Xinhua He ; Shaomin Yang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-7d673466c7891c8b6e2cf47fdd3b5c7e18c02a24f333c31bb4fcf735b254d803</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Analytical models</topic><topic>Approximation algorithms</topic><topic>Automation</topic><topic>Bayesian methods</topic><topic>bayesian networks</topic><topic>Cognition</topic><topic>command automation system</topic><topic>Inference algorithms</topic><topic>Mathematical model</topic><topic>quantitative assessment</topic><topic>survivability</topic><topic>uncertainty reasoning</topic><toplevel>online_resources</toplevel><creatorcontrib>Rulin Hu</creatorcontrib><creatorcontrib>Xinhua He</creatorcontrib><creatorcontrib>Shaomin Yang</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Rulin Hu</au><au>Xinhua He</au><au>Shaomin Yang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Research of Command Automation System Survivability Assessment Model</atitle><btitle>2010 Third International Conference on Intelligent Networks and Intelligent Systems</btitle><stitle>icinis</stitle><date>2010-11</date><risdate>2010</risdate><spage>676</spage><epage>679</epage><pages>676-679</pages><isbn>9781424485482</isbn><isbn>1424485487</isbn><eisbn>9780769542492</eisbn><eisbn>0769542492</eisbn><abstract>Based on the structural complexity of command automation system, starting from command automation system itself and the relationship between system and its environment, survivability analysis of command automation system is divided into three sub-problems of system services, external environment and model construction to be analyzed respectively. Therefore, it simplifies the complexity of the problem. Based on the uncertainty of survivability assessment information of command automation system, Bayesian network is introduced into model construction. This paper demonstrates the model construction process of command automation system survivability assessment by an example. This method has a good operability. It can not only quantitatively calculate the survivability probability of command automation system, but can also identify the major environmental factors affecting the system and the weak links of the system by diagnostic reasoning.</abstract><pub>IEEE</pub><doi>10.1109/ICINIS.2010.122</doi><tpages>4</tpages></addata></record> |
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| subjects | Analytical models Approximation algorithms Automation Bayesian methods bayesian networks Cognition command automation system Inference algorithms Mathematical model quantitative assessment survivability uncertainty reasoning |
| title | Research of Command Automation System Survivability Assessment Model |
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