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Soft Computing: State of the Art Theory and Novel Applications pp 113–128Cite as

Social Network Analysis of Co-fired Fuzzy Rules

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 291))

Abstract

The popularity of modern online social networks has grown up so quickly in the last few years that, nowadays, social network analysis has become one of the hottest research lines in the world. It is important to highlight that social network analysis is not limited to the analysis of networks connecting people. Indeed, it is strongly connected with the classical methods widely recognized in the context of graph theory. Thus, social network analysis is applied to many different areas like for instance economics, bibliometrics, and so on. This contribution shows how it can also be successfully applied in the context of designing interpretable fuzzy systems. The key point consists of looking at the rule base of a fuzzy system as a fuzzy inference-gram (fingram), i.e., as a social network made of nodes representing fuzzy rules. In addition, nodes are connected through edges that represent the interaction between rules, at inference level, in terms of co-fired rules, i.e., rules fired at the same time by a given input vector. In short, fingram analysis consists of studying the interaction among nodes in the network for the purpose of understanding the structure and behavior of the fuzzy rule base under consideration. It is based on the basic principles of social network analysis which have been properly adapted to the design of fuzzy systems.

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Author information

Authors and Affiliations

  1. Department of Electronics, University of Alcala, Madrid, Spain

    Jose M. Alonso

  2. European Centre for Soft Computing, Mieres, Asturias, Spain

    David P. Pancho, O. Cordón, A. Quirin & L. Magdalena

  3. DECSAI and CITIC-UGR, Granada, Spain

    O. Cordón

Authors
  1. Jose M. Alonso
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  2. David P. Pancho
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  3. O. Cordón
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  4. A. Quirin
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  5. L. Magdalena
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Corresponding author

Correspondence to Jose M. Alonso .

Editor information

Editors and Affiliations

  1. , Iona College, Machine Intelligence Institute, New Rochelle, 10801, New York, USA

    Ronald R. Yager

  2. Information Technologies of the, Republic of Azerbaijan, Ministry of Communications and, Zarifa Aliyeva str. 33, Baku, AZ1000, Azerbaijan

    Ali M. Abbasov

  3. , Department of Electrical, University of Alberta, ECERF Building W5-023, Edmonton, T6G 2V4, Alberta, Canada

    Marek Z. Reformat

  4. , Department of Information Technology, Azerbaijan Technical University, 25 H.Cavid Ave., Baku, AZ1073, Azerbaijan

    Shahnaz N. Shahbazova

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Alonso, J.M., Pancho, D.P., Cordón, O., Quirin, A., Magdalena, L. (2013). Social Network Analysis of Co-fired Fuzzy Rules. In: Yager, R., Abbasov, A., Reformat, M., Shahbazova, S. (eds) Soft Computing: State of the Art Theory and Novel Applications. Studies in Fuzziness and Soft Computing, vol 291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34922-5_9

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  • DOI: https://doi.org/10.1007/978-3-642-34922-5_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34921-8

  • Online ISBN: 978-3-642-34922-5

  • eBook Packages: EngineeringEngineering (R0)

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