Please use this identifier to cite or link to this item:
https://dair.nps.edu/handle/123456789/2635
Title: | Leveraging Structural Characteristics of Interdependent Networks to Model Non-linear Cascading Characteristics |
Authors: | Anita Raja |
Keywords: | Major Defense Acquisition Program (MDAP) Networks |
Issue Date: | 29-Jun-2015 |
Publisher: | Acquisiton Research Program |
Citation: | Published--Unlimited Distribution |
Series/Report no.: | Acquisition Strategy TCU-AM-15-112 |
Abstract: | The overarching goal of our multi-year research agenda is to proactively model the non-linear cascading effects of interdependencies in Major Defense Acquisition Program (MDAP) networks. This document captures the progress that my team and I have made for the duration of this project. Specifically, we discuss the decision support architecture we describe our progress towards a scalable, automated approach for extracting and analyzing the data in the form of Selected Acquisition Reports (SAR) and Defense Acquisition Executive Summaries documents of a network of MDAPs to support a decision-theoretic risk prediction model. Automation is necessitated by the volume and complexity of the data. We will discuss the role of topic modeling, image extraction and identification of topological features of the MDAP network in this approach. |
Description: | Acquisition Management / Grant-funded Research |
URI: | https://dair.nps.edu/handle/123456789/2635 |
Appears in Collections: | Sponsored Acquisition Research & Technical Reports |
Files in This Item:
File | Size | Format | |
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TCU-AM-15-112.pdf | 1.73 MB | Adobe PDF | View/Open |
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