scholarly journals A granular computing framework for approximate reasoning in situation awareness

2016 ◽  
Vol 2 (3) ◽  
pp. 141-158 ◽  
Author(s):  
Giuseppe D’Aniello ◽  
Angelo Gaeta ◽  
Vincenzo Loia ◽  
Francesco Orciuoli
Author(s):  
Lech Polkowski ◽  
Maria Semeniuk-Polkowska

Granular computing, initiated by Lotfi A. Zadeh, has acquired wide popularity as a tool for approximate reasoning, fusion of knowledge, cognitive computing. The need for formal methods of granulation, and means for computing with granules, has been addressed in this work by applying methods of rough mereology. Rough mereology is an extension of mereology taking as the primitive notion the notion of a part to a degree. Granules are formed as classes of objects which are a part to a given degree of a given object. In addition to an exposition of this mechanism of granulation, we point also to some applications like granular logics for approximate reasoning and classifiers built from granulated data sets.


2016 ◽  
Vol 1 (2) ◽  
pp. 127-143 ◽  
Author(s):  
Vincenzo Loia ◽  
Giuseppe D’Aniello ◽  
Angelo Gaeta ◽  
Francesco Orciuoli

2016 ◽  
Vol 9 (1) ◽  
pp. 151-164 ◽  
Author(s):  
Giuseppe D’Aniello ◽  
Angelo Gaeta ◽  
Matteo Gaeta ◽  
Stefania Tomasiello

Author(s):  
Angelo Gaeta ◽  
Vincenzo Loia ◽  
Francesco Orciuoli

AbstractThis paper presents a comprehensive model for representing and reasoning on situations to support decision makers in Intelligence analysis activities. The main result presented in the paper stems from a work of refinement and abstraction of previous results of the authors related to the use of Situation Awareness and Granular Computing for the development of analysis methods and techniques to support Intelligence. This work made it possible to derive the characteristics of the model from previous case studies and applications with real data, and to link the reasoning techniques to concrete approaches used by intelligence analysts such as, for example, the Structured Analytic Techniques. The model allows to represent an operational situation according to three complementary perspectives: descriptive, relational and behavioral. These three perspectives are instantiated on the basis of the principles and methods of Granular Computing, mainly based on the theories of fuzzy and rough sets, and with the help of further structures such as graphs. As regards the reasoning on the situations thus represented, the paper presents four methods with related case studies and applications validated on real data.


2018 ◽  
Vol 122 ◽  
pp. 226-237 ◽  
Author(s):  
SK Alamgir Hossain ◽  
Md. Anisur Rahman ◽  
M. Anwar Hossain

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