Contact:
Room: 155
Position:
Full Professor
Research teams:
Nowe systemy głębokiego uczenia i ich zastosowania
Classes:
Bezpieczeństwo komunikacji elektronicznej lab
Bezpieczeństwo komunikacji elektronicznej wyk
Podstawy sieci komputerowych wyk
Prof. PhD DSc Eng
Robert Nowicki
Office hours: wtorek 14:00-14:45, środa 15:15-16:00 - p. 155
Papers (78)
2021 (1)
Nowicki R.K., Seliga R., elasko D., Hayashi Y., Performance Analysis of Rough Set-Based Hybrid Classification Systems in the Case of Missing Values. (5)
Performance Analysis of Rough Set-Based Hybrid Classification Systems in the Case of Missing Values
, Performance Analysis of Rough Set-Based Hybrid Classification Systems in the Case of Missing Values, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 307-318, 2021, Cites: 52020 (1)
Nowicki R.K., Grzanek K., Hayashi Y., Rough Support Vector Machine for Classification with Interval and Incomplete Data. (15)
Rough Support Vector Machine for Classification with Interval and Incomplete Data
, Rough Support Vector Machine for Classification with Interval and Incomplete Data, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 47-56, 2020, Cites: 152019 (15)
Nowicki R.K., Fuzzy Rough Classification Systems. (0)
Fuzzy Rough Classification Systems
, Fuzzy Rough Classification Systems, Studies in Computational Intelligence, 802, 802, 71-93, 2019, Cites: 0
Rutkowski T., Lapa K., Nowicki R., Nielek R., Grzanek K., On Explainable Recommender Systems Based on Fuzzy Rule Generation Techniques. (8)
On Explainable Recommender Systems Based on Fuzzy Rule Generation Techniques
, On Explainable Recommender Systems Based on Fuzzy Rule Generation Techniques, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 358-372, 2019, Cites: 8
Nowicki R.K., Introduction. (0)
Introduction
, Introduction, Studies in Computational Intelligence, 802, 802, 1-6, 2019, Cites: 0
Nowicki R.K., Ensembles of Rough Set–Based Classifiers. (0)
Ensembles of Rough Set–Based Classifiers
, Ensembles of Rough Set–Based Classifiers, Studies in Computational Intelligence, 802, 802, 161-184, 2019, Cites: 0
Starczewski J.T., Nowicki R.K., Nieszporek K., Fuzzy-rough fuzzification in general FL classifiers. (3)
Fuzzy-rough fuzzification in general FL classifiers
, Fuzzy-rough fuzzification in general FL classifiers, IJCCI 2019 - Proceedings of the 11th International Joint Conference on Computational Intelligence, 335-342, 2019, Cites: 3
Nowicki R.K., Starczewski J.T., Grycuk R., Extended Possibilistic Fuzzification for Classification. (0)
Extended Possibilistic Fuzzification for Classification
, Extended Possibilistic Fuzzification for Classification, International Joint Conference on Computational Intelligence, 1, 1, 343-350, 2019, Cites: 0
Nowicki R.K., Rough Set Theory Fundamentals. (4)
Rough Set Theory Fundamentals
, Rough Set Theory Fundamentals, Studies in Computational Intelligence, 802, 802, 7-16, 2019, Cites: 4
Korytkowski M., Nowak J., Nowicki R., Milkowska K., Scherer M., Goetzen P., Sequential Data Mining of Network Traffic in URL Logs. (0)
Sequential Data Mining of Network Traffic in URL Logs
, Sequential Data Mining of Network Traffic in URL Logs, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 125-130, 2019, Cites: 0
Nowicki R.K., Final Remarks. (0)
Final Remarks
, Final Remarks, Studies in Computational Intelligence, 802, 802, 185-188, 2019, Cites: 0
Starczewski J.T., Nowicki R.K., Nieszporek K., Fuzzy–rough Fuzzification in General FL Classifiers. (0)
Fuzzy–rough Fuzzification in General FL Classifiers
, Fuzzy–rough Fuzzification in General FL Classifiers, International Joint Conference on Computational Intelligence, 1, 1, 335-342, 2019, Cites: 0
Nowicki R.K., Rough Nearest Neighbour Classifier. (2)
Rough Nearest Neighbour Classifier
, Rough Nearest Neighbour Classifier, Studies in Computational Intelligence, 802, 802, 133-159, 2019, Cites: 2
Nowicki R.K., Starczewski J.T., Grycuk R., Extended possibilistic fuzzification for classification. (1)
Extended possibilistic fuzzification for classification
, Extended possibilistic fuzzification for classification, IJCCI 2019 - Proceedings of the 11th International Joint Conference on Computational Intelligence, 343-350, 2019, Cites: 1
Nowicki R.K., Rough Fuzzy Classification Systems. (3)
Rough Fuzzy Classification Systems
, Rough Fuzzy Classification Systems, Studies in Computational Intelligence, 802, 802, 17-70, 2019, Cites: 3
Grycuk R., Najgebauer P., Nowicki R., Scherer R., Multilayer architecture for content-based image retrieval systems. (1)
Multilayer architecture for content-based image retrieval systems
, Multilayer architecture for content-based image retrieval systems, Proceedings - 2019 IEEE 12th Conference on Service-Oriented Computing and Applications, SOCA 2019, 119-126, 2019, Cites: 1
Nowicki R.K., Rough Neural Network Classifier. (0)
Rough Neural Network Classifier
, Rough Neural Network Classifier, Studies in Computational Intelligence, 802, 802, 95-132, 2019, Cites: 02018 (3)
Nowicki R.K., Korytkowski M., Scherer R., Rough neural network ensemble for interval data classification. (3)
Rough neural network ensemble for interval data classification
, Rough neural network ensemble for interval data classification, IEEE International Conference on Fuzzy Systems, 2018-July, 2018-July, 2018, Cites: 3
Olas T., Mleczko W.K., Wozniak M., Nowicki R.K., Gepner P., Performance evaluation of DBN learning on intel multi- and manycore architectures. (0)
Performance evaluation of DBN learning on intel multi- and manycore architectures
, Performance evaluation of DBN learning on intel multi- and manycore architectures, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10777 LNCS, 10777 LNCS, 565-575, 2018, Cites: 0
Nowak J., Korytkowski M., Nowicki R., Scherer R., Siwocha A., Random forests for profiling computer network users. (11)
Random forests for profiling computer network users
, Random forests for profiling computer network users, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 734-739, 2018, Cites: 112017 (2)
Nowicki R.K., Starczewski J.T., A new method for classification of imprecise data using fuzzy rough fuzzification. (25)
A new method for classification of imprecise data using fuzzy rough fuzzification
, A new method for classification of imprecise data using fuzzy rough fuzzification, Information Sciences, 414, 414, 33-52, 2017, Cites: 25
Kapuscinski T., Nowicki R.K., Napoli C., Comparison of effectiveness of multi-objective genetic algorithms in optimization of invertible S-boxes. (11)
Comparison of effectiveness of multi-objective genetic algorithms in optimization of invertible S-boxes
, Comparison of effectiveness of multi-objective genetic algorithms in optimization of invertible S-boxes, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 466-476, 2017, Cites: 112016 (9)
Mleczko W.K., Nowicki R.K., Angryk R., Rough restricted Boltzmann machine -New architecture for incomplete input data. (2)
Rough restricted Boltzmann machine -New architecture for incomplete input data
, Rough restricted Boltzmann machine -New architecture for incomplete input data, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 114-125, 2016, Cites: 2
Olas T., Mleczko W.K., Nowicki R.K., Wyrzykowski R., Adaptation of deep belief networks to modern multicore architectures. (5)
Adaptation of deep belief networks to modern multicore architectures
, Adaptation of deep belief networks to modern multicore architectures, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9573, 9573, 459-472, 2016, Cites: 5
Kapuscinski T., Nowicki R.K., Napoli C., Application of genetic algorithms in the construction of invertible substitution boxes. (16)
Application of genetic algorithms in the construction of invertible substitution boxes
, Application of genetic algorithms in the construction of invertible substitution boxes, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 380-391, 2016, Cites: 16
Wozniak M., Gabryel M., Nowicki R.K., Nowak B.A., An application of firefly algorithm to position traffic in NoSQL database systems. (16)
An application of firefly algorithm to position traffic in NoSQL database systems
, An application of firefly algorithm to position traffic in NoSQL database systems, Advances in Intelligent Systems and Computing, 416, 416, 259-272, 2016, Cites: 16
Nowicki R.K., Scherer R., Rutkowski L., Novel rough neural network for classification with missing data. (5)
Novel rough neural network for classification with missing data
, Novel rough neural network for classification with missing data, 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016, 820-825, 2016, Cites: 5
Kempa W.M., Wozniak M., Nowicki R.K., Gabryel M., Damasevicius R., Transient solution for queueing delay distribution in the GI/M/1/K-type mode with “queued” waking up and balking. (6)
Transient solution for queueing delay distribution in the GI/M/1/K-type mode with “queued” waking up and balking
, Transient solution for queueing delay distribution in the GI/M/1/K-type mode with “queued” waking up and balking, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 340-351, 2016, Cites: 6
Grycuk R., Gabryel M., Nowicki R., Scherer R., Content-based image retrieval optimization by differential evolution. (17)
Content-based image retrieval optimization by differential evolution
, Content-based image retrieval optimization by differential evolution, 2016 IEEE Congress on Evolutionary Computation, CEC 2016, 86-93, 2016, Cites: 17
Wozniak M., Marszalek Z., Gabryel M., Nowicki R.K., Preprocessing large data sets by the use of quick sort algorithm. (23)
Preprocessing large data sets by the use of quick sort algorithm
, Preprocessing large data sets by the use of quick sort algorithm, Advances in Intelligent Systems and Computing, 364, 364, 111-121, 2016, Cites: 23
Nowicki R.K., Nowak B.A., Wozniak M., Application of rough sets in k nearest neighbours algorithm for classification of incomplete samples. (13)
Application of rough sets in k nearest neighbours algorithm for classification of incomplete samples
, Application of rough sets in k nearest neighbours algorithm for classification of incomplete samples, Advances in Intelligent Systems and Computing, 416, 416, 243-257, 2016, Cites: 132015 (8)
Nowak B.A., Nowicki R.K., Wozniak M., Napoli C., Multi-class nearest neighbour classifier for incomplete data handling. (39)
Multi-class nearest neighbour classifier for incomplete data handling
, Multi-class nearest neighbour classifier for incomplete data handling, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 469-480, 2015, Cites: 39
Wozniak M., Polap D., Nowicki R.K., Napoli C., Pappalardo G., Tramontana E., Novel approach toward medical signals classifier. (38)
Novel approach toward medical signals classifier
, Novel approach toward medical signals classifier, Proceedings of the International Joint Conference on Neural Networks, 2015-September, 2015-September, 2015, Cites: 38
Nowicki R.K., Korytkowski M., Nowak B.A., Scherer R., Design methodology for rough neuro-fuzzy classification with missing data. (5)
Design methodology for rough neuro-fuzzy classification with missing data
, Design methodology for rough neuro-fuzzy classification with missing data, Proceedings - 2015 IEEE Symposium Series on Computational Intelligence, SSCI 2015, 1650-1657, 2015, Cites: 5
Wozniak M., Polap D., Gabryel M., Nowicki R.K., Napoli C., Tramontana E., Can we process 2D images using artificial bee colony?. (39)
Can we process 2D images using artificial bee colony?
, Can we process 2D images using artificial bee colony?, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 660-671, 2015, Cites: 39
Napoli C., Pappalardo G., Tramontana E., Nowicki R.K., Starczewski J.T., Wozniak M., Toward work groups classification based on probabilistic neural network approach. (38)
Toward work groups classification based on probabilistic neural network approach
, Toward work groups classification based on probabilistic neural network approach, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 79-89, 2015, Cites: 38
Mleczko W.K., Kapuscinski T., Nowicki R.K., Rough deep belief network - application to incomplete handwritten digits pattern classification. (18)
Rough deep belief network - application to incomplete handwritten digits pattern classification
, Rough deep belief network - application to incomplete handwritten digits pattern classification, Communications in Computer and Information Science, 538, 538, 400-411, 2015, Cites: 18
Olas T., Mleczko W.K., Nowicki R.K., Wyrzykowski R., Krzyzak A., Adaptation of RBM learning for intel MIC architecture. (7)
Adaptation of RBM learning for intel MIC architecture
, Adaptation of RBM learning for intel MIC architecture, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 90-101, 2015, Cites: 7
Wozniak M., Napoli C., Tramontana E., Capizzi G., Lo Sciuto G., Nowicki R.K., Starczewski J.T., A multiscale image compressor with RBFNN and Discrete Wavelet decomposition. (38)
A multiscale image compressor with RBFNN and Discrete Wavelet decomposition
, A multiscale image compressor with RBFNN and Discrete Wavelet decomposition, Proceedings of the International Joint Conference on Neural Networks, 2015-September, 2015-September, 2015, Cites: 382014 (5)
Wozniak M., Kempa W.M., Gabryel M., Nowicki R.K., A finite-buffer queue with a single vacation policy: An analytical study with evolutionary positioning. (46)
A finite-buffer queue with a single vacation policy: An analytical study with evolutionary positioning
, A finite-buffer queue with a single vacation policy: An analytical study with evolutionary positioning, International Journal of Applied Mathematics and Computer Science, 24, 24, 887-900, 2014, Cites: 46
Wozniak M., Kempa W.M., Gabryel M., Nowicki R.K., Shao Z., On applying evolutionary computation methods to optimization of vacation cycle costs in finite-buffer queue. (32)
On applying evolutionary computation methods to optimization of vacation cycle costs in finite-buffer queue
, On applying evolutionary computation methods to optimization of vacation cycle costs in finite-buffer queue, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 480-491, 2014, Cites: 32
Starczewski J.T., Nowicki R.K., Nowak B.A., Genetic fuzzy classifier with fuzzy rough sets for imprecise data. (8)
Genetic fuzzy classifier with fuzzy rough sets for imprecise data
, Genetic fuzzy classifier with fuzzy rough sets for imprecise data, IEEE International Conference on Fuzzy Systems, 1382-1389, 2014, Cites: 8
Nowak B.A., Nowicki R.K., Starczewski J.T., Marvuglia A., The learning of neuro-fuzzy classifier with fuzzy rough sets for imprecise datasets. (10)
The learning of neuro-fuzzy classifier with fuzzy rough sets for imprecise datasets
, The learning of neuro-fuzzy classifier with fuzzy rough sets for imprecise datasets, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 256-266, 2014, Cites: 10
Nowicki R.K., Nowak B.A., Starczewski J.T., Cpalka K., The learning of neuro-fuzzy approximator with fuzzy rough sets in case of missing features. (10)
The learning of neuro-fuzzy approximator with fuzzy rough sets in case of missing features
, The learning of neuro-fuzzy approximator with fuzzy rough sets in case of missing features, Proceedings of the International Joint Conference on Neural Networks, 3759-3766, 2014, Cites: 102013 (4)
Cpalka K., Rebrova O., Nowicki R., Rutkowski L., On design of flexible neuro-fuzzy systems for nonlinear modelling. (67)
On design of flexible neuro-fuzzy systems for nonlinear modelling
, On design of flexible neuro-fuzzy systems for nonlinear modelling, International Journal of General Systems, 42, 42, 706-720, 2013, Cites: 67
Wozniak M., Marszalek Z., Gabryel M., Nowicki R.K., Modified merge sort algorithm for large scale data sets. (28)
Modified merge sort algorithm for large scale data sets
, Modified merge sort algorithm for large scale data sets, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 612-622, 2013, Cites: 28
Nowak B.A., Nowicki R.K., Mleczko W.K., A new method of improving classification accuracy of decision tree in case of incomplete samples. (8)
A new method of improving classification accuracy of decision tree in case of incomplete samples
, A new method of improving classification accuracy of decision tree in case of incomplete samples, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 448-458, 2013, Cites: 8
Gabryel M., Nowicki R.K., Wozniak M., Kempa W.M., Genetic cost optimization of the GI/M/1/N finite-buffer queue with a single vacation policy. (29)
Genetic cost optimization of the GI/M/1/N finite-buffer queue with a single vacation policy
, Genetic cost optimization of the GI/M/1/N finite-buffer queue with a single vacation policy, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 12-23, 2013, Cites: 292012 (3)
Nowak B.A., Nowicki R.K., Learning in rough-neuro-fuzzy system for data with missing values. (3)
Learning in rough-neuro-fuzzy system for data with missing values
, Learning in rough-neuro-fuzzy system for data with missing values, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7203 LNCS, 7203 LNCS, 501-510, 2012, Cites: 3
Gabryel M., Wozniak M., K. Nowicki R., Creating learning sets for control systems using an evolutionary method. (26)
Creating learning sets for control systems using an evolutionary method
, Creating learning sets for control systems using an evolutionary method, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7269 LNCS, 7269 LNCS, 206-213, 2012, Cites: 26
Rutkowski L., Cpalka K., Nowicki R., Pokropinska A., Scherer R., Neuro-fuzzy systems. (2)
Neuro-fuzzy systems
, Neuro-fuzzy systems, Computational Complexity: Theory, Techniques, and Applications, 9781461418009, 9781461418009, 2069-2081, 2012, Cites: 22011 (2)
Korytkowski M., Nowicki R., Rutkowski L., Scherer R., AdaBoost ensemble of DCOG rough-neuro-fuzzy systems. (25)
AdaBoost ensemble of DCOG rough-neuro-fuzzy systems
, AdaBoost ensemble of DCOG rough-neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6922 LNAI, 6922 LNAI, 62-71, 2011, Cites: 25
Cpalka K., Rebrova O., Nowicki R., Rutkowski L., On designing of flexible neuro-fuzzy systems for nonlinear modelling. (2)
On designing of flexible neuro-fuzzy systems for nonlinear modelling
, On designing of flexible neuro-fuzzy systems for nonlinear modelling, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6743 LNAI, 6743 LNAI, 147-154, 2011, Cites: 22010 (3)
Korytkowski M., Nowicki R.K., Scherer R., Rutkowski L., MICOG defuzzification rough-neuro-fuzzy system ensemble. (5)
MICOG defuzzification rough-neuro-fuzzy system ensemble
, MICOG defuzzification rough-neuro-fuzzy system ensemble, 2010 IEEE World Congress on Computational Intelligence, WCCI 2010, 2010, Cites: 5
Nowicki R.K., On classification with missing data using rough-neuro-fuzzy systems. (36)
On classification with missing data using rough-neuro-fuzzy systems
, On classification with missing data using rough-neuro-fuzzy systems, International Journal of Applied Mathematics and Computer Science, 20, 20, 55-67, 2010, Cites: 36
Nowicki R.K., Starczewski J.T., On non-singleton fuzzification with DCOG defuzzification. (7)
On non-singleton fuzzification with DCOG defuzzification
, On non-singleton fuzzification with DCOG defuzzification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6113 LNAI, 6113 LNAI, 168-174, 2010, Cites: 72009 (3)
Nowicki R., Nonlinear modelling and classification based on the MICOG defuzzification. (16)
Nonlinear modelling and classification based on the MICOG defuzzification
, Nonlinear modelling and classification based on the MICOG defuzzification, Nonlinear Analysis, Theory, Methods and Applications, 71, 71, 2009, Cites: 16
Korytkowski M., Nowicki R., Scherer R., Neuro-fuzzy rough classifier ensemble. (27)
Neuro-fuzzy rough classifier ensemble
, Neuro-fuzzy rough classifier ensemble, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5768 LNCS, 5768 LNCS, 817-823, 2009, Cites: 27
Nowicki R., Rough neuro-fuzzy structures for classification with missing data. (62)
Rough neuro-fuzzy structures for classification with missing data
, Rough neuro-fuzzy structures for classification with missing data, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 39, 39, 1334-1347, 2009, Cites: 622008 (5)
Starczewski J., Scherer R., Korytkowski M., Nowicki R., Modular type-2 neuro-fuzzy systems. (21)
Modular type-2 neuro-fuzzy systems
, Modular type-2 neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4967 LNCS, 4967 LNCS, 570-578, 2008, Cites: 21
Scherer R., Korytkowski M., Nowicki R., Rutkowski L., Modular rough neuro-fuzzy systems for classification. (3)
Modular rough neuro-fuzzy systems for classification
, Modular rough neuro-fuzzy systems for classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4967 LNCS, 4967 LNCS, 540-548, 2008, Cites: 3
Morkowski M., Nowicki R., Information theory inspired weighted immune classification algorithm. (0)
Information theory inspired weighted immune classification algorithm
, Information theory inspired weighted immune classification algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 652-660, 2008, Cites: 0
Nowicki R., On combining neuro-fuzzy architectures with the rough set theory to solve classification problems with incomplete data. (44)
On combining neuro-fuzzy architectures with the rough set theory to solve classification problems with incomplete data
, On combining neuro-fuzzy architectures with the rough set theory to solve classification problems with incomplete data, IEEE Transactions on Knowledge and Data Engineering, 20, 20, 1239-1253, 2008, Cites: 44
Korytkowski M., Nowicki R., Scherer R., Rutkowski L., Ensemble of rough-neuro-fuzzy systems for classification with missing features. (14)
Ensemble of rough-neuro-fuzzy systems for classification with missing features
, Ensemble of rough-neuro-fuzzy systems for classification with missing features, IEEE International Conference on Fuzzy Systems, 1745-1750, 2008, Cites: 142007 (1)
Cpalka K., Nowicki R., Rutkowski L., Rough-neuro-fuzzy systems for classification. (3)
Rough-neuro-fuzzy systems for classification
, Rough-neuro-fuzzy systems for classification, Proceedings of the 2007 IEEE Symposium on Foundations of Computational Intelligence, FOCI 2007, 1-8, 2007, Cites: 32006 (4)
Pokropinska A., Nowicki R., Scherer R., Isolines of statistical information criteria for relational neuro-fuzzy system design. (1)
Isolines of statistical information criteria for relational neuro-fuzzy system design
, Isolines of statistical information criteria for relational neuro-fuzzy system design, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4029 LNAI, 4029 LNAI, 288-296, 2006, Cites: 1
Korytkowski M., Nowicki R., Rutkowski L., Scherer R., Merging ensemble of neuro-fuzzy systems. (7)
Merging ensemble of neuro-fuzzy systems
, Merging ensemble of neuro-fuzzy systems, IEEE International Conference on Fuzzy Systems, 1954-1957, 2006, Cites: 7
Nowicki R., Rough-neuro-fuzzy system with MICOG defuzzification. (24)
Rough-neuro-fuzzy system with MICOG defuzzification
, Rough-neuro-fuzzy system with MICOG defuzzification, IEEE International Conference on Fuzzy Systems, 1958-1965, 2006, Cites: 24
Korytkowski M., Nowicki R., Rutkowski L., Scherer R., Combining logical-type neuro-fuzzy systems. (1)
Combining logical-type neuro-fuzzy systems
, Combining logical-type neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4029 LNAI, 4029 LNAI, 240-249, 2006, Cites: 12004 (6)
Nowicki R., Pokropinska A., Hayashi Y., On designing of neuro-fuzzy systems. (1)
On designing of neuro-fuzzy systems
, On designing of neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3019, 3019, 641-649, 2004, Cites: 1
Nowicki R., Neuro-fuzzy versus non-parametric approach to system modeling and classification. (0)
Neuro-fuzzy versus non-parametric approach to system modeling and classification
, Neuro-fuzzy versus non-parametric approach to system modeling and classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3019, 3019, 632-640, 2004, Cites: 0
Nowicki R., Rough sets in the neuro-fuzzy architectures based on monotonic fuzzy implications. (19)
Rough sets in the neuro-fuzzy architectures based on monotonic fuzzy implications
, Rough sets in the neuro-fuzzy architectures based on monotonic fuzzy implications, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 510-517, 2004, Cites: 19
Korytkowski M., Gabryel M., Nowicki R., Scherer R., Genetic algorithm for database indexing. (4)
Genetic algorithm for database indexing
, Genetic algorithm for database indexing, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 1142-1147, 2004, Cites: 4
Nowicki R., Pokropinska A., Information criterions applied to neuro-fuzzy architectures design. (19)
Information criterions applied to neuro-fuzzy architectures design
, Information criterions applied to neuro-fuzzy architectures design, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 332-337, 2004, Cites: 19
Nowicki R., Rough sets in the neuro-fuzzy architectures based on non-monotonic fuzzy implications. (22)
Rough sets in the neuro-fuzzy architectures based on non-monotonic fuzzy implications
, Rough sets in the neuro-fuzzy architectures based on non-monotonic fuzzy implications, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 518-525, 2004, Cites: 222003 (1)
Nowicki R., Scherer R., Rutkowski L., A Hierarchical Neuro-Fuzzy System Based on S-Implications. (5)
A Hierarchical Neuro-Fuzzy System Based on S-Implications
, A Hierarchical Neuro-Fuzzy System Based on S-Implications, Proceedings of the International Joint Conference on Neural Networks, 1, 1, 321-325, 2003, Cites: 52002 (1)
Rutkowska D., Nowicki R., Hayashi Y., Parallel processing by implication-based neuro-fuzzy systems. (4)
Parallel processing by implication-based neuro-fuzzy systems
, Parallel processing by implication-based neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2328, 2328, 599-607, 2002, Cites: 42001 (1)
Rutkowska D., Rutkowski L., Nowicki R., Neuro-fuzzy systems with inference based on bounded product. (5)
