An Evolving Cascade Neuro-Fuzzy System for Data Stream Fuzzy Clustering

An evolving cascade neuro-fuzzy system and its online learning procedure are proposed in this paper. The system is based on nodes of a special type. A quality estimation process is defined by finding an optimal value of the used cluster validity index. Keywords— Evolving cascade system, neuro-fuzzy network, data stream, fuzzy clustering.

[1]  Eyke Hüllermeier,et al.  Online clustering of parallel data streams , 2006, Data Knowl. Eng..

[2]  Edwin Lughofer,et al.  Evolving Fuzzy Systems - Methodologies, Advanced Concepts and Applications , 2011, Studies in Fuzziness and Soft Computing.

[3]  James C. Bezdek,et al.  Fuzzy Kohonen clustering networks , 1994, Pattern Recognit..

[4]  Richard Weber,et al.  A methodology for dynamic data mining based on fuzzy clustering , 2005, Fuzzy Sets Syst..

[5]  Paramasivan Saratchandran,et al.  Sequential Adaptive Fuzzy Inference System (SAFIS) for nonlinear system identification and prediction , 2006, Fuzzy Sets Syst..

[6]  Ming-Syan Chen,et al.  Adaptive Clustering for Multiple Evolving Streams , 2006, IEEE Transactions on Knowledge and Data Engineering.

[7]  Nikola K. Kasabov,et al.  Ensembles of EFuNNs: an architecture for a multimodule classifier , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

[8]  Korris Fu-Lai Chung,et al.  Fuzzy competitive learning , 1994, Neural Networks.

[9]  Witold Pedrycz,et al.  Collaborative clustering with the use of Fuzzy C-Means and its quantification , 2008, Fuzzy Sets Syst..

[10]  T. Martin McGinnity,et al.  An on-line algorithm for creating self-organizing fuzzy neural networks , 2004, Neural Networks.

[11]  Chin-Teng Lin,et al.  An online self-constructing neural fuzzy inference network and its applications , 1998, IEEE Trans. Fuzzy Syst..

[12]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[13]  James M. Keller,et al.  A possibilistic approach to clustering , 1993, IEEE Trans. Fuzzy Syst..

[14]  Plamen P. Angelov,et al.  PANFIS: A Novel Incremental Learning Machine , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[15]  Nikola K. Kasabov,et al.  DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction , 2002, IEEE Trans. Fuzzy Syst..

[16]  Nikola K. Kasabov,et al.  Evolving fuzzy neural networks for supervised/unsupervised online knowledge-based learning , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[17]  Petri Vuorimaa.  Use of the Fuzzy Self-Organizing Map in pattern recognition , 1994, Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference.

[18]  Yevgeniy V. Bodyanskiy.  Computational Intelligence Techniques for Data Analysis , 2005, Leipziger Informatik-Tage.

[19]  P. Angelov,et al.  Evolving Fuzzy Systems from Data Streams in Real-Time , 2006, 2006 International Symposium on Evolving Fuzzy Systems.

[20]  Plamen Angelov,et al.  Evolving Takagi‐Sugeno Fuzzy Systems from Streaming Data (eTS+) , 2010 .

[21]  Gerardo Beni,et al.  A Validity Measure for Fuzzy Clustering , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  Plamen P. Angelov,et al.  Data-driven evolving fuzzy systems using eTS and FLEXFIS: comparative analysis , 2008, Int. J. Gen. Syst..

[23]  Petri Vuorimaa,et al.  Fuzzy self-organizing map , 1994 .

[24]  P. Angelov,et al.  Two approaches to data-driven design of evolving fuzzy systems: eTS and FLEXFIS , 2005, NAFIPS 2005 - 2005 Annual Meeting of the North American Fuzzy Information Processing Society.

[25]  Yevgeniy Bodyanskiy,et al.  An evolving neuro-fuzzy system for online fuzzy clustering , 2015, 2015 Xth International Scientific and Technical Conference "Computer Sciences and Information Technologies" (CSIT).

[26]  Issam J. Dagher.  Gradient based fuzzy c-means algorithm , 1994 .

[27]  MSc Frsnz Nikola Kasabov PhD.  Evolving Connectionist Systems , 2003, Perspectives in Neural Computing.

[28]  Xiaoyi Gao,et al.  Human population structure detection via multilocus genotype clustering , 2007, BMC Genetics.

[29]  Plamen P. Angelov,et al.  Simpl_eTS: a simplified method for learning evolving Takagi-Sugeno fuzzy models , 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..

[30]  Oleksii K. Tyshchenko,et al.  A hybrid cascade neural network with an optimized pool in each cascade , 2015, Soft Comput..

[31]  Christian Lebiere,et al.  The Cascade-Correlation Learning Architecture , 1989, NIPS.