Evidential Force Aggregation

TL;DR

This paper introduces an evidential force aggregation method that classifies intelligence reports into recognized force structures by measuring fitness between templates and fused intelligence, handling uncertainty and nonspecific data.

Contribution

It presents a novel classification approach that aggregates intelligence at multiple hierarchical levels using a fitness measure for uncertain and nonspecific reports.

Findings

Effective classification of force structures from uncertain intelligence reports

Handles nonspecific propositions in intelligence data

Achieves hierarchical force structure recognition

Abstract

In this paper we develop an evidential force aggregation method intended for classification of evidential intelligence into recognized force structures. We assume that the intelligence has already been partitioned into clusters and use the classification method individually in each cluster. The classification is based on a measure of fitness between template and fused intelligence that makes it possible to handle intelligence reports with multiple nonspecific and uncertain propositions. With this measure we can aggregate on a level-by-level basis, starting from general intelligence to achieve a complete force structure with recognized units on all hierarchical levels.