Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/1505
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dc.contributor.authorAnita Raja
dc.contributor.authorMohammad Rashedul Hasan
dc.contributor.authorRobert Flowe
dc.contributor.authorBrendan Fernes
dc.date.accessioned2020-03-16T17:59:10Z-
dc.date.available2020-03-16T17:59:10Z-
dc.date.issued2016-05-05
dc.identifier.citationPublished--Unlimited Distribution
dc.identifier.urihttps://dair.nps.edu/handle/123456789/1505-
dc.descriptionAcquisition Management / Defense Acquisition Community Contributor
dc.description.abstractThe overall goal of this paper is to continue our efforts to forge new ground in identifying the effects of interdependencies in large complex networked applications and, if needed, uncovering early indicators of interdependency risk so that appropriate risk mitigation actions may be taken. Specifically, we seek to study and quantify the impact of network characteristics on cascading risk. Cascading risk is defined as the propagation of programmatic issues across networked programs due to the interdependency of one program upon the other. Harnessing the extensive data that has been collected over the years in the form of Defense Acquisition Execution Summary (DAES) and Selected Acquisition Reports (SARs) documents for Major Defense Acquisition Programs (MDAPS), we will present our intermediate results in our ongoing efforts on leveraging network structure and sequential data to study cascading risks. We will also identify the challenges to data acquisition.
dc.description.sponsorshipAcquisition Research Program
dc.languageEnglish (United States)
dc.publisherAcquisition Research Program
dc.relation.ispartofseriesRisk Management
dc.relation.ispartofseriesSYM-AM-16-053
dc.subjectData Acquisition
dc.subjectInterdependent Networks
dc.titleModeling Uncertainty and Its Implications in Complex Interdependent Networks
dc.typeArticle
Appears in Collections:Annual Acquisition Research Symposium Proceedings & Presentations

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