Granular Computing for human-centred systems modelling
The main achievement of this research programme is gathering together and
systematising the fundamentals, methodologies, algorithms and representative
applications of Granular Computing. Information granules, as the name itself stipulates,
are collections of entities, usually originating at the numeric level, that are
arranged together due to their similarity, functional adjacency, indistinguishability,
coherency or alike (Pedrycz, 2001; Bargiela, 2001; Pedrycz and Bargiela, 2002,
Zadeh, 1979, 1997; Zadeh and Kacprzyk, 1999; Pedrycz and Vukovich, 1999;
Pedrycz and Smith, 1999, Pedrycz, Smith, Bargiela, 2001). Information granules as
abstractions of our reality are aimed at building efficient and user-centred views
of the external world and supporting and facilitating our perception of the surrounding
physical and virtual world. This is well appreciated by looking at some representative
areas with which information granulation is inherently associated.
The research contributed to the development of methodology for
- Construction of information granules. This process deals both with the selection
of the formal framework of information granulation and detailed estimation procedure
producing information granules. The latter dwells on the usage of the setting in which
the granules are constructed.
- Characterization of dimension (granularity) of information granules. This task is
crucial as providing us with a better insight as to the essence of the granulation
process and its implications both at the level of the methodology of the design of
the ensuing granular model as well as its usage.
- The development of the encoding and decoding mechanisms. These are essential to
the functioning of any granular architecture. The encoding and decoding schemes are
essential to the performance of granular computing. Interestingly, the essence of
information compatibility expressed in terms of its granularity is inherently related
with granular computing and nonexistent within other environments.
- The issues of interoperability are crucial to the design of systems operating
within the realm of various formalisms of information granularity.
Publications
- Bargiela A., Pedrycz W., Granular Computing for human-centred systems modelling, EPSRC GR/R10707, Final report.
- Bargiela, A., Pedrycz, W., (2002), Granular Computing: An Introduction, Kluwer Academic Publishers.
- Bargiela, A. (2001) Interval and ellipsoidal uncertainty in water system state estimation, in: Granular Computing, (Pedrycz, W., ed.), Physica Verlag, 23-57.
- Bargiela A., Pedrycz W., Tanaka M., (2003), A study of uncertain state estimation, IEEE Trans. on Systems Man and Cybernetics, SMC-A, 33, 3, 288-301.
- Bargiela, A., Pedrycz, W., (2003), Recursive information granulation: Aggregation and interpretation issues, IEEE Trans. on Systems Man and Cybernetics SMC-B, 33, 1, 96-112
- Bargiela, A., Pedrycz, W., Hirota, K. (2002), Logic-based granular prototyping, Computers Software and Applications Conference, COMPSAC 2002, Oxford, August 2002.
- Bargiela, A. Pedrycz, W., (2002), Archives of Control Sciences – Special Issue on Granular Computing, ISSN 0004-072X.
- Pedrycz, W., Smith M.H., Bargiela, A. (2000), Granular clustering: A granular signature of data, Proc. 19th Int. (IEEE) Conf. NAFIPS’2000, Atlanta, July 2000, 69-73.
- Pedrycz, W., Vukovich, G. (1999), Quantification of fuzzy mappings: a relevance of rule-based architectures, Proc. 18th Int Conf of the North American Fuzzy Information Processing Society (NAFIPS), New York, June 1-12, 105-109.
- Pedrycz W., ed. (2001), Granular Computing: An Emerging Paradigm, Physica-Verlag.
- Pedrycz, W., Bargiela, A. (2002), Granular clustering: A granular signature of data, IEEE Trans. on Systems Man and Cybernetics, Vol 32, No. 2, 212-224.
- Pedrycz W, Bargiela A, (2003), Fuzzy fractal dimensions and fuzzy modeling, Information Sciences, 153, 199-216
- Zadeh, L. A. (1979), Fuzzy sets and information granularity, In: M.M. Gupta, R.K. Ragade, R.R. Yager, eds., Advances in Fuzzy Set Theory and Applications, North Holland, Amsterdam, 3-18.
- Zadeh, L. A. (1997), Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic, Fuzzy Sets and Systems, 90, 111-117.
- Zadeh, L. A., Kacprzyk, J. (1999), Computing with Words in Information/Intelligent Systems, vol. 1-2, Physica-Verlag, Heidelberg.