Representation of multi-connected system of Fuzzy State Space Modeling (FSSM) in potential method based on a network context

Authors

  • Jibril Aminu Universiti Teknologi Malaysia
  • Tahir Ahmad Universiti Teknologi Malaysia
  • Surajo Sulaiman Universiti Teknologi Malaysia

DOI:

https://doi.org/10.11113/mjfas.v13n4.545

Keywords:

FSSM, Potential method, Feeder, Common Feeder, Greatest Common Feeder

Abstract

The complexity of a system of Fuzzy State Space Modeling (FSSM) is the reason that leads to the main objective of this research. A multi-connected system of Fuzzy State Space Model is made up of several components, each of which performs a function. These components are interconnected in some manner and determine how the overall system operates. In this study, we study the concept of graph, network system and network projections which are the requisite knowledge to potential method. Finally, the multi-connected system of FSSM of type A namely feeder, common feeder and greatest common feeder are transformed into potential method using various method of transformation.

References

Ahmad, T. (1998). Mathematical and fuzzy modeling of interconnection in integrated circuit. Doctor of Philosophy Thesis, Sheffield Hallam University, Sheffield, United Kingdom.

Caklovic, L. (2002). Decision making by potential method. Preprint.

Caklovic, L. (2003). Graph distance in multicriteria decision making context. Metodološki zvezki, 19, 25-34.

Ismail, R. (2005). Fuzzy state space modeling for solving inverse problems of multi-variable dynamic systems. Doctor of Philosophy Thesis. Universiti Teknologi Malaysia, Johor, Malaysia.

Newman, M. E. J. (2001). Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. Physical Review E, 64, 016132.

Newman, M. E. J. (2003). The structure and function of complex networks. Society for Industial and Applied Mathematics, 45(2), 167-256.

Opsahl, T. (2013). Triadic Closure in two-mode networks: Redefining the global and local clustering coefficients. Social Networks 35, doi: 10.1016/j.socnet.2011.07.001

Paraskevopoulos, P. N. (2002). Modern control engineering. New York: Marcel Dekker.

Padrón, B., Nogales, M., Traveset, A. (2011). Alternative approaches of transforming bimodal into unimodal mutualistic networks. The usefulness of preserving weighted information. Basic and Applied Ecology, 12(8), 713-721.

Taufiq A., K. (2007). Some aspects of number theory approach on the multi-connect systems of fuzzy state space model. Master Dissertation. Universiti Teknologi Malaysia.

Zadeh, L. A. (1965). Fuzzy sets. Information and Control 8.3: 338-353.

Downloads

Published

26-12-2017