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Publikacje w roku 2016

Strona główna » Publikacje » Publikacje w roku 2016

Artykuły w czasopismach z listy A MNiSW
[1] Al-Hmouz R., Pedrycz W.: Models of time series with time granulation. KNOWLEDGE AND INFORMATION SYSTEMS, vol. 48, No. 3, 2016, ss. 561-580 (JCR).
[2] Aliev R., Pedrycz W., Kreinovich V., Huseynov O.: The general theory of decisions. INFORMATION SCIENCES, vol. 327, 2016, ss. 125-148, 72 poz. bibl. (JCR).
[3] Amigo R., Giusti S., Novotny A., Silva E., Sokołowski J.: OPTIMUM DESIGN OF FLEXTENSIONAL PIEZOELECTRIC ACTUATORS INTO TWO SPATIAL DIMENSIONS. SIAM JOURNAL ON CONTROL AND OPTIMIZATION, vol. 54, No. 2, 2016, ss. 760-789 (JCR).
[4] An S., Hu Q., Pedrycz W., Zhu P., Tsang E.: Data-distribution-aware fuzzy rough set model and its application to robust classification. IEEE TRANSACTIONS ON CYBERNETICS, vol. 46, No. 12, 2016, ss. 3073-3085 (JCR).
[5] Bartkiewicz L., Szeląg B., Studziński J.: Ocena wpływu zmiennych wejściowych oraz struktury modelu sztucznej sieci neuronowej na prognozowanie dopływu ścieków komunalnych do oczyszczalni. OCHRONA ŚRODOWISKA, vol. 38, No. 2, 2016, ss. 29-36, 29 poz. bibl. (JCR).
[6] Baumert M., Porta A., Cichocki A.: Biomedical Signal Processing: From a Conceptual Framework to Clinical Applications. PROCEEDINGS OF THE IEEE, vol. 104, No. 2, 2016, ss. 220-222, 12 poz. bibl. (JCR).
[7] Bednarczuk E., Tretiakow A.: On reductibility of Degenerate Optimization Problems to Regular Operator Equations. COMPUTATIONAL MATHEMATICS AND MATHEMATICAL PHYSICS, vol. 56, No. 12, 2016, ss. 1992-2000, 14 poz. bibl. (JCR).
[8] Beliakov G., Gągolewski M., James S.: Penalty-based and other representations of economic inequality. INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS, vol. 24, No. Suppl1, 2016, ss. 1-23, 52 poz. bibl. (JCR).
[9] Blanco F., Merigo J., Kacprzyk J.: Bonferroni means with distance measures and the adequacy coefficient in entrepreneurial group theory. KNOWLEDGE-BASED SYSTEMS, vol. 111, 2016, ss. 217-227, 30 poz. bibl. (JCR).
[10] Branke J., Corrente S., Greco S., Słowiński R., Zielniewicz P.: Using Choquet Integral as Preference Model in Interactive Evolutionary Multiobjective Optimization. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, vol. 250, No. 250, 2016, ss. 884-901 (JCR).
[11] Brezhneva O., Tretiakow A.: New Approach to Optimality Conditions for Degenerate Nonlinear Programming Problems. DOKLADY MATHEMATICS, vol. 93, No. 2, 2016, ss. 166-169 (JCR).
[12] Caixeta A., Lasiecka I., Cavalcanti V.: On long time behavior of Moore-Gibson-Thompson equation with molecular relaxation. EVOLUTION EQUATIONS AND CONTROL THEORY, vol. 5, No. 4, 2016, ss. 661-676 (JCR).
[13] Carnevale C., Douros J., Finzi G., Graff A., Guariso G., Nahorski Z., Pisoni E., Ponche J., Real E., Turrini E., Vlachostas C.: Uncertainty evaluation in air quality planning decisions: a case study for Northern Italy. ENVIRONMENTAL SCIENCE & POLICY, vol. 65, 2016, ss. 39-47, 65 poz. bibl. (JCR).
[14] Cavalcanti M., Correa W., Lasiecka I., Lefler C.: Wellposedness and uniform stability for nonlinear Shroedinger equations with dynamic/Wentzell boundary conditions. INDIANA UNIVERSITY MATHEMATICS JOURNAL , vol. 65, No. 5, 2016, ss. 1445-1502 (JCR).
[15] Chen L., Jin J., Daly I., Zhang Y., Wang X., Cichocki A.: Exploring combinations of different color and facial expression stimuli for gaze-independent BCIs. FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, vol. 10, 2016, ss. 1-11, 44 poz. bibl. (JCR).
[16] Chichin S., Vo Q., Kowalczyk R.: Towards efficient and truthful market mechanisms for double-sided cloud markets. IEEE TRANSACTIONS ON SERVICES COMPUTING, 2016, 36 poz. bibl. (JCR).
[17] Chris C., Nguyen H., Pal S., Wei Zhi W., Skowron A.: Preface. FUNDAMENTA INFORMATICAE, vol. 142, No. 1-4, 2016, ss. v-viii (JCR).
[18] Chueshov I., Dowell E., Lasiecka I., Webster J.: Nonlinear Elastic Plate in a Flow of Gas:Recent Results and Conjectures. APPLIED MATHEMATICS AND OPTIMIZATION, vol. 73, No. 3, 2016, ss. 475-500 (JCR).
[19] Corrente S., Greco S., Kadziński M., Słowiński R.: Inducing probability distributions on the set of value functions by Subjective Stochastic Ordinal Regression. KNOWLEDGE-BASED SYSTEMS, vol. 112, No. 112, 2016, ss. 26-36 (JCR).
[20] Dell-Oro F., Lasiecka I., Pata V.: The Moore-Gibson-Thompson equation with memory in the critical case. JOURNAL OF DIFFERENTIAL EQUATIONS, vol. 261, No. 7, 2016, ss. 4188-4222 (JCR).
[21] Fan K., Pedrycz W.: Opinion evolution influenced by informed agents. PHYSICA A: STATISTICAL MECHANICS AND ITS APPLICATIONS, vol. 462, 2016, ss. 431-441 (JCR).
[22] Feng F., Cho J., Pedrycz W., Fujita H., Herawan T.: Soft set based association rule mining. KNOWLEDGE-BASED SYSTEMS, vol. 111, No. 111, 2016, ss. 268-282, 27 poz. bibl. (JCR).
[23] Gągolewski M., Bartoszuk M., Cena A.: Genie: A new, fast, and outlier-resistant hierarchical clustering algorithm. INFORMATION SCIENCES, vol. 363, 2016, ss. 8-23 (JCR).
[24] Greco S., Słowiński R., Szczęch I.: Measures of rule interestingness in four perspectives of confirmation. INFORMATION SCIENCES, No. 346-347, 2016, ss. 216-235 (JCR).
[25] Gwak J., Jeon M., Pedrycz W.: Bolstering efficient SSGAs based on an ensemble of probabilistic variable-wise crossover strategies. SOFT COMPUTING, vol. 20, No. 6, 2016, ss. 2149-2176 (JCR).
[26] Holnicki-Szulc P., Kałuszko A., Trapp W.: An urban scale application and validation of the CALPUFF model. ATMOSPHERIC POLLUTION RESEARCH, vol. 7, No. 3, 2016, ss. 393-402, 31 poz. bibl. (JCR).
[27] Homenda W., Jastrzębska A., Pedrycz W.: Multicriteria decision making inspired by human cognitive processes. APPLIED MATHEMATICS AND COMPUTATION, vol. 290, 2016, ss. 392-411 (JCR).
[28] Hryniewicz O.: Bayes statistical decisions with random fuzzy data - an application in reliability. RELIABILITY ENGINEERING & SYSTEM SAFETY, vol. 151, No. 1, 2016, ss. 20-33, 85 poz. bibl. (JCR).
[29] Hryniewicz O., Kaczmarek K.: Bayesian analysis of time series using granular computing approach. APPLIED SOFT COMPUTING, vol. 47, 2016, ss. 644-652 (JCR).
[30] Hu J., Pedrycz W., Wang G., Wang K.: Rough sets in distributed decision information systems. KNOWLEDGE-BASED SYSTEMS, vol. 94, 2016, ss. 13-22 (JCR).
[31] Hu X., Pedrycz W., Wang X.: Optimal allocation of information granularity in system modeling through the maximization of information specificity: A development of granular input space. APPLIED SOFT COMPUTING, vol. 42, No. 42, 2016, ss. 410-422, 25 poz. bibl. (JCR).
[32] Isazadeh A., Mahan F., Pedrycz W.: MFlexDT: multi flexible fuzzy decision tree for data stream classification. SOFT COMPUTING, vol. 20, 2016, ss. 3719-3733 (JCR).
[33] Jabłecki J., Gątarek D.: Modeling joint defaults in correlation-sensitive instruments. JOURNAL OF CREDIT RISK, vol. 12, No. 3, 2016, ss. 15-42, 15 poz. bibl. (JCR).
[34] Kacprzyk J., Zadrożny S.: Fuzzy logic-based linguistic summaries of time series: a powerful tool for discovering knowledge on time varying processes and systems under imprecision. WILEY INTERDISCIPLINARY REVIEWS: DATA MINING AND KNOWLEDGE DISCOVERY , vol. 6, No. 1, 2016, ss. 37-46, 40 poz. bibl. (JCR).
[35] Kadziński M., Ciomek K., Rychły P., Słowiński R.: Post factum analysis for robust multiple criteria ranking and sorting. JOURNAL OF GLOBAL OPTIMIZATION, vol. 65, No. 3, 2016, ss. 531-562, 45 poz. bibl. (JCR).
[36] Kaliszewski I., Kiczkowiak T., Miroforidis J.: Mechanical design, Multiple Criteria Decision Making and Pareto optimality gap. ENGINEERING COMPUTATIONS, vol. 33, No. 3, 2016, ss. 876-895, 23 poz. bibl. (JCR).
[37] Kaliszewski I., Podkopaev D.: Simple Additive Weighting - a metamodel for Multiple Criteria Decision Analysis methods. EXPERT SYSTEMS WITH APPLICATIONS, vol. 54, 2016, ss. 155-161, 17 poz. bibl. (JCR).
[38] Karczmarek P., Pedrycz W., Kiersztyn A., Rutka P.: A study in facial features saliency in face recognition: an analytic hierarchy process approach. SOFT COMPUTING, 2016, ss. 1-15 (JCR).
[39] Kołacz A., Grzegorzewski P.: Measures of dispersion for multidimensional data. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, vol. 251, 2016, ss. 930-937, 13 poz. bibl. (JCR).
[40] Kowalski P., Kulczycki P.: A Complete Algorithm for the Reduction of Pattern Data in the Classification of Interval Information. INTERNATIONAL JOURNAL OF COMPUTATIONAL METHODS , vol. 13, No. 3, 2016, ss. 1650018-1-1650018-26, 29 poz. bibl. (JCR).
[41] Kowalski P., Łukasik S.: Training Neural Networks with Krill Herd Algorithm. NEURAL PROCESSING LETTERS, vol. 44, No. 1, 2016, ss. 5-17, 27 poz. bibl. (JCR).
[42] Kruś L., Woroniecka-Leciejewicz I.: Analysis of strategies in a monetary-fiscal game. The case of Poland. CONTROL AND CYBERNETICS, vol. 45, No. 2, 2016, ss. 163-183, 22 poz. bibl. (JCR).
[43] Kułakowski K., Kulczycki P., Misztal K., Dydejczyk A., Gronek P., Krawczyk M.: Naming boys after presidents in U.S. in 20th century. ACTA PHYSICA POLONICA A, vol. 129, No. 5, 2016, ss. 1038-1044, 20 poz. bibl. (JCR).
[44] Lasek J., Szlavik Z., Gągolewski M., Bhulai S.: How to improve a team's position in the FIFA ranking – A simulation study. JOURNAL OF APPLIED STATISTICS, vol. 43, No. 7, 2016, ss. 1349-1368, 41 poz. bibl. (JCR).
[45] Lasiecka I., Cavalcanti V., Caixeta A.: Global attractors for a third order in time nonlinear dynamics. JOURNAL OF DIFFERENTIAL EQUATIONS, vol. 261, No. 1, 2016, ss. 113-147 (JCR).
[46] Lasiecka I., Triggiani R.: Heat-structure interaction with viscoelastic damping: analyticity with sharp analytic sector, exponential decay, fractional powers. COMMUNICATIONS ON PURE AND APPLIED ANALYSIS, vol. 15, No. 5, 2016, ss. 1515-1543 (JCR).
[47] Lasiecka I., Triggiani R.: Heat-wave interaction in 2-3 dimensions: optimal rational decay rate. JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS, No. 2, 2016, ss. 782-815 (JCR).
[48] Lasiecka I., Wang X.: Moore-Gibson-Thompson equation with memory, part I: exponential decay of energy. ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND PHYSIK, vol. 67, No. 2, 2016, ss. 2-23 (JCR).
[49] Lasiecka I., Webster J.: Feedback stabilization of a fluttering panel in an inviscid subsonic potential flow. SIAM JOURNAL ON MATHEMATICAL ANALYSIS, vol. 48, No. 3, 2016, ss. 1848-1891 (JCR).
[50] Lasiecka I., Webster J.: Stabilization of a nonlinear flow-plate interaction via component-wise decomposition. BULLETIN OF THE BRAZILIAN MATHEMATICAL SOCIETY, vol. 47, No. 2, 2016, ss. 489-506 (JCR).
[51] Lei X., Wang F., Wu F., Pedrycz W., Zhang A.: Protein complex identification through Markov clustering with firefly algorithm on dynamic protein–protein interaction networks. INFORMATION SCIENCES, vol. 329, 2016, ss. 303-316, 45 poz. bibl. (JCR).
[52] Li J., Li C., Cichocki A.: Canonical Polyadic Decomposition with Auxiliary Information for Brain Computer Interface. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2015 [druk w 2016 roku], ss. 1-9, 34 poz. bibl. (JCR).
[53] Livi L., Tahayori H., Rizzi A., Sadeghian A., Pedrycz W.: Classification of type-2 fuzzy sets represented as sequences of vertical slices. IEEE TRANSACTIONS ON FUZZY SYSTEMS, vol. 24, No. 5, 2016, ss. 1022-1034, 61 poz. bibl. (JCR).
[54] Lu W., Zhang L., Pedrycz W., Yang J., Liu X.: The granular extension of Sugeno-type fuzzy models based on optimal allocation of information granularity and its application to forecasting of time series. APPLIED SOFT COMPUTING, vol. 42, 2016, ss. 38-52 (JCR).
[55] Malinowski J.: Reliability Analysis of a Flow Network with a Series-Parallel-Reducible Structure. IEEE TRANSACTIONS ON RELIABILITY, vol. 65, No. 2, 2016, ss. 851-859, 26 poz. bibl. (JCR).
[56] Mesiar R., Gągolewski M.: H-index and Other Sugeno Integrals: Some Defects and Their Compensation. IEEE TRANSACTIONS ON FUZZY SYSTEMS, vol. 24, No. 6, 2016, ss. 1668-1672, 21 poz. bibl. (JCR).
[57] Myśliński A.: Piecewise constant level set method for topology optimization of unilateral contact problems. ADVANCES IN ENGINEERING SOFTWARE, vol. 80, 2015 [druk w 2016 roku], ss. 25-32, 33 poz. bibl. (JCR).
[58] Ng W., Zeng G., Zhang J., Yeung D., Pedrycz W.: Dual autoencoders features for imbalance classification problem. PATTERN RECOGNITION, vol. 60, 2016, ss. 875-889 (JCR).
[59] Nguyen D., Nguyen L., Vo B., Pedrycz W.: Efficient mining of class association rules with the itemset constraint. KNOWLEDGE-BASED SYSTEMS, vol. 103, 2016, ss. 73-88 (JCR).
[60] Nguyen H., Vo B., Nguyen M., Pedrycz W.: An efficient algorithm for mining frequent weighted itemsets using interval word segments. APPLIED INTELLIGENCE, vol. 45, No. 4, 2016, ss. 1008-1020 (JCR).
[61] Nowak P., Hryniewicz O.: On generalized versions of central limit theorems for IF-events. INFORMATION SCIENCES, vol. 355-356, 2016, ss. 299-313 (JCR).
[62] Opara K., Hryniewicz O.: Computation of general correlation coefficients for interval data. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, vol. 73, 2016, ss. 56-75, 35 poz. bibl. (JCR).
[63] Opara K., Skakuj M., Stöckner M.: Factors affecting raveling of motorway pavements—A field experiment with new additives to the deicing brine. CONSTRUCTION AND BUILDING MATERIALS, vol. 113, 2016, ss. 174-187, 28 poz. bibl. (JCR).
[64] Osmolovskii N.: Necessary second-order conditions for a weak local minimum in a problem with endpoint and control constraints. JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS, vol. 457, No. 2, 2018 (w wersji on-line od roku 2016), s. 1613-1633 (JCR).
[65] Ouyang Y., Pedrycz W.: A new model for intuitionistic fuzzy multi-attributes decision making. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, vol. 249, No. 2, 2016, ss. 677-682, 30 poz. bibl. (JCR).
[66] Pałkowski Ł., Błaszczyński J., Skrzypczak A., Błaszczak J., Nowaczyk A., Wróblewska J., Kożuszko S., Gospodarek E., Słowiński R., Krysiński J.: Prediction of antifungal activity of gemini-imidazolium compounds. BIOMED RESEARCH INTERNATIONAL, vol. 2015, 2015 [druk w 2016 roku], ss. 1-10 (JCR).
[67] Pawłowski W., Szmeja P., Wasielewska K., Paprzycki M., Ganzha M.: Semantic interoperability in the Internet of Things: An overview from the INTER-IoT perspective. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, vol. 81, 2017 [druk w 2016 roku], ss. 111-124 (JCR).
[68] Pedrycz W., Jastrzębska A., Homenda W.: Design of fuzzy cognitive maps for modeling time series. IEEE TRANSACTIONS ON FUZZY SYSTEMS, vol. 24, No. 1, 2016, ss. 120-130, 36 poz. bibl. (JCR).
[69] Pedrycz W., Wang X.: Designing fuzzy sets with the use of the parametric principle of justifiable granularity. IEEE TRANSACTIONS ON FUZZY SYSTEMS, vol. 24, No. 2, 2016, ss. 489-496, 26 poz. bibl. (JCR).
[70] Peura M., Triviño M., Mazziotta A., Podkopaev D., Juutinen A., Mönkkönen M.: Managing boreal forests for the simultaneous production of collectable goods and timber revenues. SILVA FENNICA, vol. 50, No. 5 id 1672, 2016, ss. 1-17, 48 poz. bibl. (JCR).
[71] Pham V., Ngo L., Pedrycz W.: Interval-valued fuzzy set approach to fuzzy co-clustering for data classification. KNOWLEDGE-BASED SYSTEMS, vol. 107, 2016, ss. 1-13 (JCR).
[72] Plotnikov P., Ganghoffer J., Sokołowski J.: Volumetric material growth: Mathematical theory. DOKLADY MATHEMATICS, vol. 94, No. 2, 2016, ss. 498-501, 10 poz. bibl. (JCR).
[73] Protasiewicz J., Pedrycz W., Kozłowski M., Dadas S., Kopacz A., Gałężewska M.: A recommender system of reviewers and experts in reviewing problems. KNOWLEDGE-BASED SYSTEMS, vol. 106, 2016, ss. 164-178 (JCR).
[74] Qin J., Liu X., Pedrycz W.: A multiple attribute interval type-2 fuzzy group decision making and its application to supplier selection with extended LINMAP method. SOFT COMPUTING, 2016, ss. 1-20 (JCR).
[75] Qin J., Liu X., Pedrycz W.: Frank aggregation operators and their application to hesitant fuzzy multiple attribute decision making. APPLIED SOFT COMPUTING, vol. 41, 2016, ss. 428-452 (JCR).
[76] Reyes-Galaviz O., Pedrycz W.: Enhancement of the classification and reconstruction performance of Fuzzy C-Means with refinements of prototypes. FUZZY SETS AND SYSTEMS, 2016, ss. 1-20, 50 poz. bibl. (JCR).
[77] Roh S., Oh S., Pedrycz W., Seo K.: Development of autofocusing algorithm based on fuzzy transforms. FUZZY SETS AND SYSTEMS, vol. 288, 2016, ss. 129-144 (JCR).
[78] Rojas-Rueda D., de Nazelle A., Andersen Z., Braun-Fahrländer C., Bruha J., Bruhova-Foltynova H., Desqueyroux H., Praznoczy C., Ragettli M., Tainio M., Nieuwenhuijsen M.: Health impacts of active transportation in Europe. PLOS ONE, vol. 11, No. 3, 2016, ss. 1-14, 33 poz. bibl. (JCR).
[79] Romaniuk M.: On simulation of maintenance costs for water distribution system with fuzzy parameters. EKSPLOATACJA I NIEZAWODNOść - MAINTENANCE AND RELIABILITY, vol. 18, No. 4, 2016, ss. 514-527, 32 poz. bibl. (JCR).
[80] Skowron A., Jankowski A.: Rough Sets and Interactive Granular Computing. FUNDAMENTA INFORMATICAE, vol. 147, No. 2-3, 2016, ss. 371-385 (JCR).
[81] Szeląg B., Bartkiewicz L., Studziński J.: Zastosowanie metod czarnej skrzynki do prognozowania wartości wybranych wskaźników jakości ścieków dopływających do oczyszczalni komunalnej. OCHRONA ŚRODOWISKA, vol. 38, No. 4, 2016, ss. 39-46, 18 poz. bibl. (JCR).
[82] Szmidt E., Kacprzyk J., Bujnowski P.: How to measure the amount of knowledge conveyed by Atanassov's Intuitionistic Fuzzy Sets. INFORMATION SCIENCES, vol. 257, 2014 [druk w 2016 roku], ss. 276-285 (JCR).
[83] Świechowski M., Mańdziuk J.: Fast Interpreter for Logical Reasoning in General Game Playing. JOURNAL OF LOGIC AND COMPUTATION, vol. 26, No. 5, 2014 [druk w 2016 roku], ss. 1697-1728 (JCR).
[84] Świechowski M., Mańdziuk J., Soon Ong Y.: Specialization of a UCT-based General Game Playing Program to Single-Player Games. IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES, vol. 8, No. 3, 2016, ss. 218-228 (JCR).
[85] Taegyun J., Jongmin Y., Pedrycz W., Moongu J., Boreom L., Byeongcheol L.: Robust detection of heartbeats using association models from blood pressure and EEG signals. BIOMEDICAL ENGINEERING ONLINE, vol. 15, No. 7, 2016, ss. 1-14 (JCR).
[86] Talaśka T., Kolasa M., Długosz R., Pedrycz W.: Analog programmable distance calculation circuit for winner takes all neural network realized in the CMOS technology. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, vol. 27, No. 3, 2016, ss. 661-673, 51 poz. bibl. (JCR).
[87] Thunis P., Miranda A., Baldasano J., Blond N., Douros J., Graff A., Janssen S., Juda-Rezler K., Karvosenoja N., Maffeis G., Martilli A., Rasoloharimahefa M., Real E., Viaene P., Volta M.: Overview of current regional and local scale air quality modelling practices: Assessment and planning tools in the EU. ENVIRONMENTAL SCIENCE & POLICY, vol. 65, 2016, ss. 13-21, 57 poz. bibl. (JCR).
[88] Tichavsky P., Phan A., Cichocki A.: Partitioned Alternating Least Squares Technique for Canonical Polyadic Tensor Decomposition. IEEE SIGNAL PROCESSING LETTERS, vol. 23, No. 7, 2016, ss. 993-997, 15 poz. bibl. (JCR).
[89] Triviño M., Pohjanmies T., Mazziotta A., Juutinen A., Podkopaev D., Le Tortorec E., Mönkkönen M.: Optimizing management to enhance multifunctionality in a boreal forest landscape. JOURNAL OF APPLIED ECOLOGY, vol. 54, No. 1, 2017 [druk w 2016 roku], ss. 61-70, 55 poz. bibl. (JCR).
[90] Verstraete J.: The spatial disaggregation problem: simulating reasoning using a fuzzy inference system. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2016, ss. 1-15 (JCR).
[91] Viaene P., Belis C., Blond N., Bouland C., Juda-Rezler K., Karvosenoja N., Martilli A., Miranda A., Pisoni E., Volta M.: Air quality integrated assessment modelling in the context of EU policy. A way forward. ENVIRONMENTAL SCIENCE & POLICY, vol. 65, 2016, ss. 22-28 (JCR).
[92] Wang X., Pedrycz W., Gacek A., Liu X.: From numeric data to information granules: A design through clustering and the principle of justifiable granularity. KNOWLEDGE-BASED SYSTEMS, vol. 101, 2016, ss. 100-113 (JCR).
[93] Wu G., Pedrycz W., Ma M., Liu J., Li H.: Coordinated planning of heterogeneous earth observation resources. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS: SYSTEMS, vol. 46, No. 1, 2016, ss. 109-125, 58 poz. bibl. (JCR).
[94] Yokota T., Zhao Q., Cichocki A.: Smooth PARAFAC decomposition for tensor completion. IEEE TRANSACTIONS ON SIGNAL PROCESSING, vol. 64, No. 20, 2016, ss. 5423-5436, 82 poz. bibl. (JCR).
[95] Zhang L., Lu W., Liu X., Pedrycz W., Zhong C.: Fuzzy C-Means clustering of incomplete data based on probabilistic information granules of missing values. KNOWLEDGE-BASED SYSTEMS, vol. 99, 2016, ss. 51-70 (JCR).
[96] Zhang Y., Zhou G., Jin J., Zhao Q., Wang X., Cichocki A.: Sparse Bayesian Classification of EEG for Brain–Computer Interface. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, vol. 27, No. 11, 2016, ss. 2256-2267, 65 poz. bibl. (JCR).
[97] Zhao J., Han Z., Pedrycz W., Wang W.: Granular model of long-term prediction for energy system in steel industry. IEEE TRANSACTIONS ON CYBERNETICS, vol. 46, No. 2, 2016, ss. 388-400, 22 poz. bibl. (JCR).
[98] Zhou G., Cichocki A., Zhang Y., Mandic D.: Group Component Analysis for Multiblock Data: Common and Individual Feature Extraction. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, vol. 27, No. 11, 2016, ss. 2426-2438, 47 poz. bibl. (JCR).
[99] Zhou G., Zhao Q., Zhang Y., Adali T., Xie S., Cichocki A.: Linked Component Analysis from Matrices to High Order Tensors: Applications to Biomedical Data. PROCEEDINGS OF THE IEEE, vol. 104, No. 2, 2016, ss. 310-331, 128 poz. bibl. (JCR).
[100] Zhou J., Li X., Pedrycz W.: Mean-semi-entropy models of fuzzy portfolio selection. IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 24, No. 6, 2016, ss. 1627-1636, 40 poz. bibl. (JCR).
[101] Zhou N., Cheng H., Pedrycz W., Zhang Y., Liu H.: Discriminative sparse subspace learning and its application to unsupervised feature selection. ISA TRANSACTIONS, vol. 61, 2016, ss. 104-118 (JCR).
[102] Zhou N., Xu Y., Cheng H., Fang J., Pedrycz W.: Global and local structure preserving sparse subspace learning: An iterative approach to unsupervised feature selection. PATTERN RECOGNITION , vol. 53, 2016, ss. 87-101 (JCR).
[103] Zhou S., Jin J., Daly I., Wang X., Cichocki A.: Optimizing the Face Paradigm of BCI System by Modified Mismatch Negative Paradigm. FRONTIERS IN NEUROSCIENCE, vol. 10, 2016, ss. 1-9, 48 poz. bibl. (JCR).
[104] Zhou X., Pedrycz W., Kuang Y., Zhang Z.: Type-2 fuzzy multi-objective DEA model: An application to sustainable supplier evaluation. APPLIED SOFT COMPUTING, vol. 46, 2016, ss. 424-440 (JCR).
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