Abstract
The paper presents «Neuro-Fuzzy Library» (NFL) – a free library for fuzzy and neuro-fuzzy systems. The library written in C++ is available from the GitHub repository. The library implements data modifiers (for complete and incomplete data), clustering algorithms, fuzzy systems (descriptors, t-norms, premises, consequences, rules, and implications), neuro-fuzzy systems (precomposed MA, TSK, ANNBFIS, and subspace ANNBFIS for both classification and regression tasks). The paper is accompanied by numerical examples.
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References
Czogała, E., Łęski, J.: Fuzzy and Neuro-Fuzzy Intelligent Systems. Series in Fuzziness and Soft Computing. Springer, Heidelberg (2000). https://doi.org/10.1007/978-3-7908-1853-6
Dheeru, D., Karra Taniskidou, E.: UCI machine learning repository (2017). http://archive.ics.uci.edu/ml
Dunn, J.C.: A fuzzy relative of the ISODATA process and its use in detecting compact, well separated clusters. J. Cybern. 3(3), 32–57 (1973)
Gan, G., Wu, J.: A convergence theorem for the fuzzy subspace clustering (FSC) algorithm. Pattern Recogn. 41(6), 1939–1947 (2008). https://doi.org/10.1016/j.patcog.2007.11.011
Krishnapuram, R., Keller, J.: A possibilistic approach to clustering. IEEE Trans. Fuzzy Syst. 1, 98–110 (1993)
Leski, J.: Systemy neuronowo-rozmyte (in Polish: Neuro-fuzzy systems). Wydawnictwa Naukowo-Techniczne, Warszawa (2008)
Leski, J.M.: Fuzzy \(c\)-ordered-means clustering. Fuzzy Sets Syst. 286, 114–133 (2014). https://doi.org/10.1016/j.fss.2014.12.007
Mackey, M.C., Glass, L.: Oscillation and chaos in physiological control systems. Science 197(4300), 287–289 (1977)
Mamdani, E.H., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man-Mach. Stud. 7(1), 1–13 (1975)
Pedrycz, W.: Conditional fuzzy clustering in the design of radial basis function neural networks. IEEE Trans. Neural Netw. 9(4), 601–612 (1998)
Siminski, K.: Clustering with missing values. Fundamenta Informaticae 123(3), 331–350 (2013)
Siminski, K.: Neuro-fuzzy system with weighted attributes. Soft Comput. 18(2), 285–297 (2014). https://doi.org/10.1007/s00500-013-1057-z
Siminski, K.: Rough fuzzy subspace clustering for data with missing values. Comput. Inform. 33(1), 131–153 (2014)
Siminski, K.: Fuzzy weighted C-ordered means clustering algorithm. Fuzzy Sets Syst. 318, 1–33 (2017). https://doi.org/10.1016/j.fss.2017.01.001. http://www.sciencedirect.com/science/article/pii/S0165011417300180
Sugeno, M., Kang, G.T.: Structure identification of fuzzy model. Fuzzy Sets Syst. 28(1), 15–33 (1988)
Takagi, T., Sugeno, M.: Fuzzy identification of systems and its application to modeling and control. IEEE Trans. Syst. Man Cybern. 15(1), 116–132 (1985)
Youden, W.J.: Index for rating diagnostic tests. Cancer 3(1), 32–35 (1950)
Acknowledgements
The research has been supported by the Rector’s Grant for Research and Development (Silesian University of Technology, grant number: 02/020/RGJ19/0165).
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Siminski, K. (2019). NFL – Free Library for Fuzzy and Neuro-Fuzzy Systems. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Paving the Road to Smart Data Processing and Analysis. BDAS 2019. Communications in Computer and Information Science, vol 1018. Springer, Cham. https://doi.org/10.1007/978-3-030-19093-4_11
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DOI: https://doi.org/10.1007/978-3-030-19093-4_11
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