Research Summaries

Back Exploiting Environmental Analysis and Prediction, Queuing and Search Theory, and Modeling and Simulation to Optimize Activity-Based Collection Prioritization

Fiscal Year 2015
Division Graduate School of Engineering & Applied Science
Department Meteorology
Investigator(s) Murphree, James T.
Sponsor Department of Defense Space (DoD)
Summary In an era of ever increasing threats and ever decreasing resources, activity-based collection is vital to optimally utilize available assets and maximize the detection, classification, and interdiction of entities of concern. Thus, we propose to conduct a research and development effort in which we will:
1) Exploit advanced analysis and prediction of the physical environment (e.g., of atmospheric, oceanic, and land conditions) to narrow the temporal and geographical scope for collections (for example, use analyzed and predicted ocean surface wave and wind conditions to prioritize and optimize collections for drug running submersibles and semi-submersibles whose activities are limited by wave heights and wind speeds).
2) Take advantage of search theory to maximize search effectiveness and prioritization, while limiting the total number of search assets or time on station
3) Couple search theory with queuing theory to better understand the likelihood of success for a given level of entity and search platform activity
4) Use modeling and simulation to look for overall process limitations and sticking points, and to optimize the performance of the overall search and classification system
Keywords
Publications Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal
Data Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal