M. Y. Lee and K. C. Kwak, “An Incremental Granular Network for Data Modeling in Software Engineering,” 2010 4th International Conference on New Trends in Information Science and Service Science (NISS), Gyeongju, Korea , May 2010, pp. 495-498.
AUTHORS: Keun-Chang Kwak
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.