A Design of Incremental Granular Network for Software Data Modeling

Keun-Chang Kwak

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DOI: 10.4236/jsea.2010.311120                

Abstract

In this paper, we propose an incremental method of Granular Networks (GN) to construct conceptual and computational platform of Granular Computing (GrC). The essence of this network is to describe the associations between information granules including fuzzy sets formed both in the input and output spaces. The context within which such relationships are being formed is established by the system developer. Here information granules are built using Context-driven Fuzzy Clustering (CFC). This clustering develops clusters by preserving the homogeneity of the clustered patterns associated with the input and output space. The experimental results on well-known software module of Medical Imaging System (MIS) revealed that the incremental granular network showed a good performance in comparison to other previous literature.

Keywords

Incremental Granular Network, Granular Computing, Information Granules, Context-Based Fuzzy Clustering

Conflicts of Interest

The authors declare no conflicts of interest.

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