A Design of Incremental Granular Network for Software Data Modeling
Keun-Chang Kwak
DOI: 10.4236/jsea.2010.311120   PDF    HTML     5,276 Downloads   8,937 Views  


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.

Share and Cite:

K. Kwak, "A Design of Incremental Granular Network for Software Data Modeling," Journal of Software Engineering and Applications, Vol. 3 No. 11, 2010, pp. 1027-1031. doi: 10.4236/jsea.2010.311120.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] W. Pedrycz, A. Skowron and V. Kreinovich, “Handbook of Granular Computing,” John Wiley & Sons, Hoboken, 2008.
[2] W. Pedrycz and F. Gomide, “Fuzzy Systems Engineering: Toward Human-Centric Computing,” Wiley-Interscience, Hoboken, 2007.
[3] 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.
[4] W. Pedrycz, “Conditional Fuzzy C-Means,” Pattern Recognition Letters, Vol. 17, No. 6, May 1996, pp. 625-632.
[5] W. Pedrycz and A. V. Vasilakos, “Linguistic Models and Linguistic Modeling,” IEEE Transactions on Systems, Man and Cybernetics-Part C, Vol. 29, No. 6, 1999, pp. 745-757.
[6] W. Pedrycz and K. C. Kwak, “Linguistic Models as Framework of User-Centric System Modeling,” IEEE Transactions on Systems, Man and Cybernetics-Part A, Vol. 36, No. 4, 2006, pp. 727-745.
[7] W. Pedrycz, “Conditional Fuzzy Clustering in the Design of Radial Basis Function Neural Networks,” IEEE Transactions on Neural Networks, Vol. 9, No. 4, 1999. pp. 745-757.
[8] W. Pedrycz and K. C. Kwak, “The Development of Incremental Models,” IEEE Transactions on Fuzzy Systems, Vol. 15, No. 3, 2007, pp. 507-518.
[9] S. K. Oh, W. Pedrycz and B. J. Park, “Self-Organizing Neurofuzzy Networks in Modeling Software Data,” Fuzzy Sets and Systems, Vol. 145, No. 1, July 2004, pp. 165-181.
[10] J. Abonyi, R. Babuska and F. Szeifert, “Fuzzy Modeling with Multivariate Membership Functions: Gray-Box Identification and Control Design,” IEEE Transactions on Systems, Man and Cybernectics-Part B, Vol. 31, No. 5, 2001, pp. 755-767.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.