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Year: 2013

  • K. Cpałka, O. Rebrova, R. Nowicki and L. Rutkowski. "On design of flexible neuro-fuzzy systems for nonlinear modelling", International Journal of General Systems, Vol. 42. 2013, pp. 706-720. [More] [Online version]
  • M. Gabryel, R. K. Nowicki, M. Wo'zniak and W. M. Kempa. "", Genetic Cost Optimization of the GI/M/1/N Finite-Buffer Queue with a Single Vacation Policy, Rutkowski et al eds, Springer Berlin Heidelberg, Berlin, Heidelberg 2013, pp. 12-23. [More] [Online version]
  • B. A. Nowak, R. K. Nowicki and W. Mleczko, "A New Method of Improving Classification Accuracy of Decision Tree in Case of Incomplete Samples", Artificial Intelligence and Soft Computing, Rutkowski et al eds, Springer Berlin Heidelberg, 2013, pp. 448-458. [More] [Online version]
  • M. Wo'zniak, Z. Marszalek, M. Gabryel and R. K. Nowicki. "", Modified Merge Sort Algorithm for Large Scale Data Sets, Rutkowski et al eds, Springer Berlin Heidelberg, Berlin, Heidelberg 2013, pp. 612-622. [More] [Online version]
  • B. Nowak, R. Nowicki and W. Mleczko, "A New Method of Improving Classification Accuracy of Decision Tree in Case of Incomplete Samples", Artificial Intelligence and Soft Computing, Rutkowski et al eds, Springer Berlin Heidelberg, 2013, pp. 448-458. [More] [Online version]
  • L. Pietruczuk, P. Duda and M. Jaworski, "Adaptation of Decision Trees for Handling Concept Drift", Artificial Intelligence and Soft Computing, Rutkowski et al eds, Springer Berlin Heidelberg, 2013, pp. 459-473. [More] [Online version]

Year: 2012

  • P. Najgebauer, T. Nowak, J. Romanowski, J. Rygał, M. Korytkowski and R. Scherer. "Novel Method for Parasite Detection in Microscopic Samples". 2012. [More]
  • M. Zalasiński and K. Cpałka. "Novel algorithm for the on-line signature verification", Lecture Notes in Artificial Intelligence. 2012, pp. 362-367. [More]
  • A. Przybył and K. Cpałka. "A new method to construct of interpretable models of dynamic systems", Lecture Notes in Artificial Intelligence. 2012, pp. 697-705. [More]
  • L. Rutkowski, A. Przybył and K. Cpałka. "Novel on-line speed profile generation for industrial machine tool based on flexible neuro-fuzzy approximation", IEEE Transactions on Industrial Electronics, Vol. 59. 2012, pp. 1238-1247. [More]
  • B. A. Nowak and R. Nowicki. "Learning in rough-neuro-fuzzy system for data with missing values", Lecture Notes in Computer Science, Vol. 7203. 2012, pp. 501-510. [More] [Online version]
  • L. Bartczuk, P. Dziwi'nski and J. Starczewski. "A new method for dealing with unbalanced linguistic term set". Artificial Intelligence and Soft Computing. 2012. pp. 207-212. [More]
  • P. Dziwi'nski, L. Bartczuk and J. T. Starczewski, "Fully controllable ant colony system for text data clustering", Swarm and Evolutionary Computation, Springer, 2012, pp. 199-205. [More]
  • M. Gabryel, M. Wo'zniak and R. K. Nowicki. "", Creating Learning Sets for Control Systems Using an Evolutionary Method, Rutkowski et al eds, Springer Berlin Heidelberg, Berlin, Heidelberg 2012, pp. 206-213. [More] [Online version]
  • B. Nowak and R. Nowicki, "Learning in Rough-Neuro-Fuzzy System for Data with Missing Values", Parallel Processing and Applied Mathematics, Wyrzykowski et al eds, Springer Berlin Heidelberg, 2012, pp. 501-510. [More] [Online version]
  • M. WoŸniak, M. Gabryel and R. K. Nowicki. "Simulation of the characteristics of the ball movement on a beam by the use of genetic algorithm", Zeszyty naukowe Politechniki Œl¹skiej, Vol. 2. 2012, pp. 19-33. [More]
  • M. Jaworski and M. Gabryel, "On Learning in a Time-Varying Environment by Using a Probabilistic Neural Network and the Recursive Least Squares Method", Artificial Intelligence and Soft Computing, Rutkowski et al eds, Springer Berlin Heidelberg, 2012, pp. 99-110. [More] [Online version]
  • M. Jaworski, L. Pietruczuk and P. Duda, "On Resources Optimization in Fuzzy Clustering of Data Streams", Artificial Intelligence and Soft Computing, Rutkowski et al eds, Springer Berlin Heidelberg, 2012, pp. 92-99. [More] [Online version]
  • M. Jaworski, P. Duda and L. Pietruczuk, "On Fuzzy Clustering of Data Streams with Concept Drift", Artificial Intelligence and Soft Computing, Rutkowski et al eds, Springer Berlin Heidelberg, 2012, pp. 82-91. [More] [Online version]
  • M. Jaworski, M. Er and L. Pietruczuk, "On the Application of the Parzen-Type Kernel Regression Neural Network and Order Statistics for Learning in a Non-stationary Environment", Artificial Intelligence and Soft Computing, Rutkowski et al eds, Springer Berlin Heidelberg, 2012, pp. 90-98. [More] [Online version]
  • P. Duda, M. Jaworski and L. Pietruczuk, "On Pre-processing Algorithms for Data Stream", Artificial Intelligence and Soft Computing, Rutkowski et al eds, Springer Berlin Heidelberg, 2012, pp. 56-63. [More] [Online version]
  • L. Pietruczuk and M. J. Er. "Weak Convergence of the Parzen-type Probabilistic Neural Network Handling Time-varying Noise". Proceedings of the 11th International Conference on Artificial Intelligence and Soft Computing - Volume Part I. 2012. pp. 152-159. [More] [Online version]
  • L. Pietruczuk and Y. Hayashi, "Strong Convergence of the Recursive Parzen-Type Probabilistic Neural Network Handling Nonstationary Noise", Artificial Intelligence and Soft Computing, Rutkowski et al eds, Springer Berlin Heidelberg, 2012, pp. 160-168. [More] [Online version]
  • L. Pietruczuk, P. Duda and M. Jaworski, "A New Fuzzy Classifier for Data Streams", Artificial Intelligence and Soft Computing, Rutkowski et al eds, Springer Berlin Heidelberg, 2012, pp. 318-324. [More] [Online version]
  • M. Jaworski and Y. Hayashi, "On the Application of the Parzen-Type Kernel Probabilistic Neural Network and Recursive Least Squares Method for Learning in a Time-Varying Environment", Parallel Processing and Applied Mathematics, Wyrzykowski et al eds, Springer Berlin Heidelberg, 2012, pp. 490-500. [More] [Online version]
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