Integrating System Dynamics and Bayesian Networks with Application to Counter-IED Scenarios
Abstract
The practice of choosing a single modeling paradigm for predictive analysis can limit the scope and relevance of predictions and their utility to decision-making processes. Considering multiple modeling methods simultaneously may improve this situation, but a better solution provides a framework for directly integrating different, potentially complementary modeling paradigms to enable more comprehensive modeling and predictions, and thus better-informed decisions. The primary challenges of this kind of model integration are to bridge language and conceptual gaps between modeling paradigms, and to determine whether natural and useful linkages can be made in a formal mathematical manner. To address these challenges in the context of two specific modeling paradigms, we explore mathematical and computational options for linking System Dynamics (SD) and Bayesian network (BN) models and incorporating data into the integrated models. We demonstrate that integrated SD/BN models can naturally be described as either state space equations or Dynamic Bayes Nets, which enables the use of many existing computational methods for simulation and data integration. To demonstrate, we apply our model integration approach to techno-social models of insurgent-led attacks and security force counter-measures centered on improvised explosive devices.
- Authors:
- Publication Date:
- Research Org.:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1006304
- Report Number(s):
- PNNL-SA-70858
TRN: US201105%%930
- DOE Contract Number:
- AC05-76RL01830
- Resource Type:
- Conference
- Resource Relation:
- Conference: 10th International Probabilistic Safety Assessment & Management Conference - PSAM10, June 7-11, 2010, Seattle, WA
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEFENSE; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; DECISION MAKING; EXPLOSIVES; DETECTION; PROBABILISTIC ESTIMATION; RISK ASSESSMENT; COMPUTERIZED SIMULATION; SYSTEMS ANALYSIS; SABOTAGE; MILITARY STRATEGY
Citation Formats
Jarman, Kenneth D, Brothers, Alan J, Whitney, Paul D, Young, Jonathan, and Niesen, David A. Integrating System Dynamics and Bayesian Networks with Application to Counter-IED Scenarios. United States: N. p., 2010.
Web.
Jarman, Kenneth D, Brothers, Alan J, Whitney, Paul D, Young, Jonathan, & Niesen, David A. Integrating System Dynamics and Bayesian Networks with Application to Counter-IED Scenarios. United States.
Jarman, Kenneth D, Brothers, Alan J, Whitney, Paul D, Young, Jonathan, and Niesen, David A. 2010.
"Integrating System Dynamics and Bayesian Networks with Application to Counter-IED Scenarios". United States.
@article{osti_1006304,
title = {Integrating System Dynamics and Bayesian Networks with Application to Counter-IED Scenarios},
author = {Jarman, Kenneth D and Brothers, Alan J and Whitney, Paul D and Young, Jonathan and Niesen, David A},
abstractNote = {The practice of choosing a single modeling paradigm for predictive analysis can limit the scope and relevance of predictions and their utility to decision-making processes. Considering multiple modeling methods simultaneously may improve this situation, but a better solution provides a framework for directly integrating different, potentially complementary modeling paradigms to enable more comprehensive modeling and predictions, and thus better-informed decisions. The primary challenges of this kind of model integration are to bridge language and conceptual gaps between modeling paradigms, and to determine whether natural and useful linkages can be made in a formal mathematical manner. To address these challenges in the context of two specific modeling paradigms, we explore mathematical and computational options for linking System Dynamics (SD) and Bayesian network (BN) models and incorporating data into the integrated models. We demonstrate that integrated SD/BN models can naturally be described as either state space equations or Dynamic Bayes Nets, which enables the use of many existing computational methods for simulation and data integration. To demonstrate, we apply our model integration approach to techno-social models of insurgent-led attacks and security force counter-measures centered on improvised explosive devices.},
doi = {},
url = {https://www.osti.gov/biblio/1006304},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Jun 06 00:00:00 EDT 2010},
month = {Sun Jun 06 00:00:00 EDT 2010}
}