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Year: 2012

  • M. Jaworski and M. Er, "Learning in a Non-stationary Environment Using the Recursive Least Squares Method and Orthogonal-Series Type Regression Neural Network", Parallel Processing and Applied Mathematics, Wyrzykowski et al eds, Springer Berlin Heidelberg, 2012, pp. 480-489. [More] [Online version]
  • P. Duda and J. Zurada, "On the Cesaro Orthogonal Series-Type Kernel Probabilistic Neural Networks Handling Non-stationary Noise", Parallel Processing and Applied Mathematics, Wyrzykowski et al eds, Springer Berlin Heidelberg, 2012, pp. 435-442. [More] [Online version]
  • J. Zurada and M. Jaworski, "Learning in a Time-Varying Environment by Making Use of the Stochastic Approximation and Orthogonal Series-Type Kernel Probabilistic Neural Network", Parallel Processing and Applied Mathematics, Wyrzykowski et al eds, Springer Berlin Heidelberg, 2012, pp. 539-548. [More] [Online version]
  • M. Er and P. Duda, "On the Weak Convergence of the Orthogonal Series-Type Kernel Regresion Neural Networks in a Non-stationary Environment", Parallel Processing and Applied Mathematics, Wyrzykowski et al eds, Springer Berlin Heidelberg, 2012, pp. 443-450. [More] [Online version]
  • L. Pietruczuk and J. Zurada, "Weak Convergence of the Recursive Parzen-Type Probabilistic Neural Network in a Non-stationary Environment", Parallel Processing and Applied Mathematics, Wyrzykowski et al eds, Springer Berlin Heidelberg, 2012, pp. 521-529. [More] [Online version]
  • L. Pietruczuk and M. Er, "Strong Convergence of the Parzen-Type Probabilistic Neural Network in a Time-Varying Environment", Parallel Processing and Applied Mathematics, Wyrzykowski et al eds, Springer Berlin Heidelberg, 2012, pp. 530-538. [More] [Online version]
  • Y. Hayashi and L. Pietruczuk. "On General Regression Neural Network in a Nonstationary Environment", Vol. 7203. 2012, pp. 461-469. [More] [Online version]

Year: 2011

  • M. Jaworski, L. Pietruczuk, P. Duda and L. Rutkowski. "On optimization of resources in stream data mining system". Selected Topics in Computer Science Applications. D. Rutkowska, A. Cader and K. Przybyszewski eds. 2011. [More]
  • P. Duda, L. Pietruczuk, L. Rutkowski and M. Jaworski. "On selection of data pre-processing procedures in stream data mining systems". Selected Topics in Computer Science Applications. D. Rutkowska, A. Cader and K. Przybyszewski eds. 2011. [More]
  • M. Jaworski, L. Pietruczuk, P. Duda and L. Rutkowski. "Fuzzy clustering for data streams". Selected Topics in Computer Science Applications. D. Rutkowska, A. Cader and K. Przybyszewski eds. 2011. [More]
  • L. Pietruczuk, L. Rutkowski, P. Duda and M. Jaworski. "Ensemble based classification in data streams". Selected Topics in Computer Science Applications. D. Rutkowska, A. Cader and K. Przybyszewski eds. 2011. [More]
  • M. Zalasiński and K. Cpałka, "A new method of on-line signature verification using a flexible fuzzy one-class classifier", Selected Topics in Computer Science Applications, Academic Publishing House EXIT, 2011, pp. 38-53. [More]
  • M. Scherer and K. Cpałka, "Neuro-fuzzy-based approach to decision making support", Selected Topics in Computer Science Applications, Academic Publishing House EXIT, 2011, pp. 200-210. [More]
  • K. Cpałka, M. Orzyłowski and L. Rutkowski. "Neuro-fuzzy structures and their applications", Some Aspects of Computer Science, Academic Publishing House EXIT, 2011, pp. 122-132. [More]
  • K. Cpałka. "New methods for designing and reduction of neuro-fuzzy systems", Journal of Applied Computer Science Methods, Vol. 2. 2011, pp. 113-126. [More]
  • R. Nowicki, J. Starczewski and M. Orzyłowski. "On non-singleton fuzzification in some neuro-fuzzy architectures", Some Aspects of Computer Science, D. Rutkowska, J. Kacprzyk, A. Cader and K. Przybyszewski eds, EXIT Academic Publishing House, Warsaw 2011, pp. 133-146. [More]
  • K. Cpałka, O. Rebrova, R. Nowicki and L. Rutkowski. "On designing of flexible neuro-fuzzy systems for nonlinear modeling", Lecture Notes in Artificial Intelligence, Vol. 6743. 2011, pp. 147-154. [More]
  • M. Korytkowski, R. Nowicki, L. Rutkowski and R. Scherer, "AdaBoost Ensemble of DCOG Rough–Neuro–Fuzzy Systems", Computational Collective Intelligence. Technologies and Applications, Jedrzejowicz, Piotr, Nguyen, Ngoc, Hoang and Kiem eds, Springer Berlin / Heidelberg, 2011, pp. 62-71. [More] [Online version]
  • M. Korytkowski, R. Nowicki, L. Rutkowski and R. Scherer. "AdaBoost Ensemble of DCOG Rough–Neuro–Fuzzy Systems", Lectures Notes in Computer Systems, Vol. 6922. 2011, pp. 62-71. [More]
  • M. Korytkowski, L. Rutkowski and R. Scherer. "Rule Base Normalization in Takagi-Sugeno Ensemble". IEEE Symposium Series on Computational Intelligence - SSCI 2011, April 11-15, 2011 - Paris, France, 2011 IEEE Workshop on Hybrid Intelligent Models and Applications. 2011. pp. 1-5. [More]
  • R. Scherer. "An Ensemble of Logical-type Neuro-fuzzy Systems", Expert Systems With Applications. 2011. [More]

Year: 2010

  • L. Rutkowski, A. Przybył, K. Cpałka and E. M. Joo. "Online Speed Profile Generation for Industrial Machine Tool Based on Neuro Fuzzy Approach", Lecture Notes in Artificial Intelligence, Vol. 6113. 2010, pp. 645-650. [More]
  • K. Cpałka, L. Rutkowski and E. M. Joo. "On Automatic Design of Neuro Fuzzy Systems", Lecture Notes in Artificial Intelligence, Vol. 6113. 2010, pp. 42-48. [More]
  • M. Gabryel, M. Korytkowski, R. Scherer, A. Pokropinska and S. Drozda. "Evolutionary Learning for Neuro-fuzzy Ensembles with Generalized Parametric Triangular Norms", Lecture Notes in Artificial Intelligence, Vol. 6113. 2010, pp. 74-79. [More] [Online version]
  • P. Dziwi'nski, J. Starczewski and L. Bartczuk. "New linguistic hedges in construction of interval type-2 FLS", Artifical Intelligence and Soft Computing. 2010, pp. 445-450. [More]
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