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publikacje w roku  

Pracownia Inteligencji Obliczeniowej - 2014

  1. P. Filipiak, P. Wnuk-Lipiński, E. Brzychczy, R. Zimroz, Artificial Immune Systems for Data Classification in Planetary Gearboxes Condition Monitoring, Advances in Condition Monitoring of Machinery in Non-Stationary Operations, Lecture Notes in Mechanical Engineering, Springer, 2014, pp. 235-247. (http://dx.doi.org/10.1007/978-3-642-39348-8_20)
  2. P. Wnuk-Lipiński, Training Complex Decision Support Systems with Differential Evolution Enhanced by Locally Linear Embedding, Applications of Evolutionary Computation, Lecture Notes in Computer Science, vol. 8602, Springer, 2014, pp. 125-137. (http://dx.doi.org/10.1007/978-3-662-45523-4_11)
  3. A. Brabazon, P. Wnuk-Lipiński, Pattern Mining in Ultra-High Frequency Order Books with Self-Organizing Maps, Applications of Evolutionary Computation, Lecture Notes in Computer Science, vol. 8602, Springer, 2014, pp. 288-298. (http://dx.doi.org/10.1007/978-3-662-45523-4_24)
  4. P. Filipiak, P. Wnuk-Lipiński, Infeasibility Driven Evolutionary Algorithm with Feed-Forward Prediction Strategy for Dynamic Constrained Optimization Problems, Applications of Evolutionary Computation, Lecture Notes in Computer Science, vol. 8602, Springer, 2014, pp. 817-828. (http://dx.doi.org/10.1007/978-3-662-45523-4_66)
  5. P. Wnuk-Lipiński, Optimizing Objective Functions with Non-Linearly Correlated Variables Using Evolution Strategies with Kernel-Based Dimensionality Reduction, Hybrid Artificial Intelligence Systems, Lecture Notes in Computer Science, vol. 8480, 2014, Springer, pp. 342-353. (http://dx.doi.org/10.1007/978-3-319-07617-1_31)
  6. P. Filipiak, K. Michalak, P. Wnuk-Lipiński, Multiobjective Dynamic Constrained Evolutionary Algorithm for Control of a Multi-segment Articulated Manipulator, Intelligent Data Engineering and Automated Learning, Lecture Notes in Computer Science, vol. 8669, 2014, pp. 199-206. (http://dx.doi.org/10.1007/978-3-319-10840-7_25)
  7. P. Filipiak, P. Wnuk-Lipiński, Univariate Marginal Distribution Algorithm with Markov Chain Predictor in Continuous Dynamic Environments, Intelligent Data Engineering and Automated Learning, Lecture Notes in Computer Science, vol. 8669, 2014, pp. 404-411. (http://dx.doi.org/10.1007/978-3-319-10840-7_49)
  8. J. Chorowski, P. Filipiak, K. Michalak, P. Wnuk-Lipiński, A. Łańcucki, Continuous Population-Based Incremental Learning with Mixture Probability Modeling for Dynamic Optimization Problems, Intelligent Data Engineering and Automated Learning, Lecture Notes in Computer Science, vol. 8669, 2014, pp. 457-464. (http://dx.doi.org/10.1007/978-3-319-10840-7_55)
  9. J. Chorowski, J. Wang, J.M. Zurada, Review and performance comparison of SVM- and ELM-based classifiers, Neurocomputing 128, 507-516. (http://dx.doi.org/10.1016/j.neucom.2013.08.009)
  10. J. Chorowski, J.M. Zurada, Learning Understandable Neural Networks With Nonnegative Weight Constraints, Transactions on Neural Networks and Learning Systems PP, 1-1. (http://dx.doi.org/doi:10.1109/TNNLS.2014.2310059)
  11. S. Dey, U. Maulik, S. Bhattacharyya, I. Saha, Multi-level Thresholding using Quantum Inspired Meta-heuristics, Knowledge-Based Systems, Vol. 67, pp. 373-400, 2014. (http://dx.doi.org/10.1016/j.knosys.2014.04.006)
  12. A. Faleńska, A. Björkelund, Ö. Cetinoglu, R. Farkas, T. Mueller, W. Seeker, Z. Szántó, Introducing the IMS-Wrocław-Szeged-CIS entry at the SPMRL 2014 Shared Task: Reranking and Morpho-syntax meet Unlabeled, Proceedings of the First Joint Workshop on Statistical Parsing of Morphologically Rich Languages and Syntactic Analysis of Non-Canonical Languages. (http://www.aclweb.org/anthology/W14-6110)
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