MECH: Algorithms and Tools for Automated Assessment of Potential Attack Locations
Abstract
This report presents the Monitor, Emplacement, and Control in a Halo (MECH) model for modeling and simulation of behaviors associated with insurgent attacks, and their relationship with geographic locations and temporal windows. Tactical operations were abstracted in terms of interobservability, distances, and logistics/shelter distance which were added with the geomorphometric measures to form a set of 77 features for analysis. An ensemble of multiple Machine Learning (ML) algorithms can classify incident vs. non-incident sites with single-digit error rates. Leading contributors of the 77 features picked by the algorithms were found to be highly consistent with that hand-picked by three military personnel with extensive deployment experience. The statistical pattern analysis method is cross checked with tactical simulations based on the MECH behavior model. The results show that they represent highly consistent results. A software prototype based on Android device and a web server was implemented to demonstrate the effectiveness of fusion of statistical pattern analysis, simulation, and human interpretation of military doctrines within the context of the two modeling approaches. It shows the feasibility of self-guided situational analysis informed by MECH-based situational awareness analytics.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 06, 2015
- Accession Number
- ADA623600
Entities
People
- B. Qu
- J. C. Liu
- Jian Lin
- S. George
- Xufeng Wang
Organizations
- Texas A&M University