Abstract
Granular Computing (GrC) is a domain of science aiming at modeling computations and reasoning that deals with imprecision, vagueness and incompleteness of information. Computations in GrC are performed on granules which are obtained as a result of information granulation. Principal issues in GrC concern processes of representation, construction, transformation and evaluation of granules. It also requires aligning with some of the fundamental computational issues concerning, e.g., interaction and adaptation. The paper outlines the current status of GrC and provides the general overview of the process of building granular solutions to challenges posed by various real-life problems involving granularity. It discusses the steps that lead from raw data and imprecise/vague specification towards a complete, useful application of granular paradigm.
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19 December 2018
The acknowledgement section of this paper originally referred to grant DEC-2013/09/B/ST6/01568. The reference to this grant has been removed from the acknowledgement section at the request of one of the authors.
References
Lin, T.Y., et al.: Granular computing - topical section. In: Meyers, R.A. (ed.) Encyclopedia of Complexity and Systems Science, pp. 4283–4435. Springer, New York (2009)
Yao, Y., Zhong, N.: Granular computing. In: Wah, B., Wah, B.M. (eds.) Wiley Encyclopedia of Computer Science and Engineering. Wiley, New York (2008)
Pedrycz, W.: History and development of granular computing. In: UNESCO-EOLSS Joint Committee, (ed.) Encyclopedia of Life Support Systems (EOLSS). Eolss Publishers, Paris (2012)
Apolloni, B., Pedrycz, W., Bassis, S., Malchiodi, D.: The Puzzle of Granular Computing. Studies in Computational Intelligence, vol. 138. Springer, Heidelberg (2008)
Bargiela, A., Pedrycz, W.: Granular Computing: An Introduction. Kluwer Academic Publishers, Dordrecht (2003)
Bello, R., Falcón, R., Pedrycz, W.: Granular Computing: At the Junction of Rough Sets and Fuzzy Sets. Studies in Fuzziness and Soft Computing, vol. 234. Springer, Heidelberg (2010)
Pedrycz, W.: Granular Computing Analysis and Design of Intelligent Systems. CRC Press, Taylor and Francis, Boca Raton (2013)
Polkowski, L., Artiemjew, P.: Granular Computing in Decision Approximation: An Application of Rough Mereology. Intelligent Systems Reference Library. Springer, Switzerland (2015)
Stepaniuk, J.: Rough-Granular Computing in Knowledge Discovery and Data Mining. Springer, Heidelberg (2008)
Inuiguchi, M., Hirano, S., Tsumoto, S. (eds.): Rough Set Theory and Granular Computing. Studies in Fuzziness and Soft Computing, vol. 125. Springer, Heidelberg (2003)
Lin, T.Y., Yao, Y., Zadeh, L.A. (eds.): Rough Sets, Granular Computing and Data Mining. Studies in Fuzziness and Soft Computing. Physica-Verlag, Heidelberg (2001)
Pal, S.K., Skowron, A. (eds.): Rough Fuzzy Hybridization: A New Trend in Decision-Making. Springer, Singapore (1999)
Pal, S.K., Polkowski, L., Skowron, A. (eds.): Rough-Neural Computing: Techniques for Computing with Words. Cognitive Technologies. Springer, Heidelberg (2004)
Pedrycz, W. (ed.): Granular Computing: An Emerging Paradigm. Studies in Fuzziness and Soft Computing, vol. 70. Physica-Verlag, Heidelberg (2001)
Pedrycz, W. (ed.): Knowledge-Based Clustering. From Data to Information Granules. Wiley, New York (2005)
Bargiela, A., Pedrycz, W. (eds.): Human-Centric Information Processing Through Granular Modelling. Studies in Computational Intelligence, vol. 182. Springer, Heidelberg (2009)
Pedrycz, W., Chen, S.M. (eds.): Granular Computing and Intelligent Systems Design with Information Granules of Higher Order and Higher Type. Studies in Computational Intelligence, vol. 502. Springer, Heidelberg (2011)
Pedrycz, W., Chen, S.M. (eds.): Information Granularity, Big Data, and Computational Intelligence. Studies in Big Data, vol. 8. Springer, Heidelberg (2015)
Yao, J.T. (ed.): Novel Developments in Granular Computing: Applications for Advanced Human Reasoning and Soft Computation. IGI Global, Hershey (2010)
Zadeh, L.A., Kacprzyk, J. (eds.): Computing with Words in Information/Intelligent Systems. Physica-Verlag, Heidelberg (1999)
Zhang, L., Zhang, B. (eds.): Quotient Space Based Problem Solving: A Theoretical Foundation of Granular Computing. Elsevier, Amsterdam (2014)
Zadeh, L.A.: Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets Syst. 90, 111–127 (1997)
Zadeh, L.A.: Generalized theory of uncertainty (GTU) - principal concepts and ideas. Comput. Stat. Data Anal. 51, 15–46 (2006)
Zadeh, L.A. (ed.): Computing with Words: Principal Concepts and Ideas. Studies in Fuzziness and Soft Computing, vol. 277. Springer, Heidelberg (2012)
Keefe, R.: Theories of Vagueness. Cambridge Studies in Philosophy. Cambridge University Press, Cambridge (2000)
Baker, G., Hacker, P.: Wittgenstein: Understanding and Meaning. Analytical Commentary on the Philosophical Investigations, Part II: Exegesis 1–184, vol. 1, 2nd edn. Wiley-Blackwell Publishing, Oxford (2004)
Zadeh, L.A.: Fuzzy logic = Computing with words. IEEE Trans. Fuzzy Syst. 2, 103–111 (1996)
Zadeh, L.A.: From computing with numbers to computing with words - from manipulation of measurements to manipulation of perceptions. IEEE Trans. Circuits Syst. 45, 105–119 (1999)
Zadeh, L.A.: Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans. Syst. Man Cybern. SMC–3, 28–44 (1973)
Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning about Data. System Theory, Knowledge Engineering and Problem Solving, vol. 9. Kluwer Academic Publishers, Dordrecht (1991)
Pawlak, Z., Skowron, A.: Rudiments of rough sets. Inf. Sci. 177(1), 3–27 (2007)
Pawlak, Z., Skowron, A.: Rough sets: some extensions. Inf. Sci. 177(1), 28–40 (2007)
Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)
Moore, R., Kearfott, R.B., Cloud, M.J.: Introduction to Interval Analysis. SIAM, Philadelphia (2009)
Pedrycz, W.: From fuzzy sets to shadowed sets: interpretation and computing. Int. J. Intell. Syst. 24(1), 48–61 (2009)
Sakai, H., Okuma, H., Nakata, M., Ślȩzak, D.: Stable rule extraction and decision making in rough non-deterministic information analysis. Int. J. Hybrid Intell. Syst. 8(1), 41–57 (2011)
Sakai, H., Wu, M., Nakata, M.: Apriori-based rule generation in incomplete information databases and non-deterministic information systems. Fundamenta Informaticae 130(3), 343–376 (2014)
Ślȩzak, D., Synak, P., Wojna, A., Wróblewski, J.: Two database related interpretations of rough approximations: data organization and query execution. Fundamenta Informaticae 127(1–4), 445–459 (2013)
Pankratieva, V.V., Kuznetsov, S.O.: Relations between proto-fuzzy concepts, crisply generated fuzzy concepts, and interval pattern structures. Fundamenta Informaticae 115(4), 265–277 (2012)
Lin, T.Y.: Data mining and machine oriented modeling: a granular computing approach. Appl. Intell. 13(2), 113–124 (2000)
Polkowski, L., Skowron, A.: Rough mereological calculi of granules: a rough set approach to computation. Comput. Intell. 17(3), 472–492 (2001)
Skowron, A., Stepaniuk, J., Peters, J.F., Świniarski, R.W.: Calculi of approximation spaces. Fundamenta Informaticae 72, 363–378 (2006)
Krasuski, A., Jankowski, A., Skowron, A., Ślȩzak, D.: From sensory data to decision making: a perspective on supporting a fire commander. In: 2013 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, Atlanta, Georgia, USA, 17–20 November 2013, Workshop Proceedings, pp. 229–236. IEEE Computer Society (2013)
Szczuka, M.S., Skowron, A., Stepaniuk, J.: Function approximation and quality measures in rough-granular systems. Fundamenta Informaticae 109(3), 339–354 (2011)
Pedrycz, W.: The principle of justifiable granularity and an optimization of information granularity allocation as fundamentals of granular computing. J. Inf. Process. Syst. 7(3), 397–412 (2011)
Apolloni, B., Pedrycz, W., Bassis, S., Malchiodi, D.: The Puzzle of Granular Computing. Studies in Computational Intelligence, vol. 138. Springer, Heidelberg (2008)
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Szczuka, M., Jankowski, A., Skowron, A., Ślęzak, D. (2015). Building Granular Systems - from Concepts to Applications. In: Yao, Y., Hu, Q., Yu, H., Grzymala-Busse, J.W. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. Lecture Notes in Computer Science(), vol 9437. Springer, Cham. https://doi.org/10.1007/978-3-319-25783-9_22
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DOI: https://doi.org/10.1007/978-3-319-25783-9_22
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