A new method for representing linguistic quantifications by random sets with applications to tracking and data fusion

W.C. Torrez1, D. Bamber2, I.R. Goodman2, H.T. Nguyen3
1CNO STRATEGIC STUDIES GROUP, NAVAL WAR College, Newport, USA
2Space and Naval Warfare Systems Center, San Diego, USA
3Department of Mathematical Sciences, New Mexico State University, Las Cruces, NM, USA

Tóm tắt

There is an obvious need to be able to integrate both linguistic-based and stochastic-based input information in data fusion. In particular, this need is critical in addressing problems of track association, including cyber-state intrusions. This paper treats this issue through a new insight into how three apparently distinct mathematical tools can be combined: "boolean relational event algebra" (BREA), "one point random set coverage representations of fuzzy sets" (OPRSC), and "complexity-reducing algorithm for near optimal fusion" (CRANOF).

Từ khóa

#Algebra #Fuzzy logic #Fuzzy sets #Educational institutions #Probabilistic logic #Arithmetic #Natural languages #Stochastic processes #Information security #Testing

Tài liệu tham khảo

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