Publikacje w roku 2014 - Instytut Badań Systemowych Polskiej Akademii Nauk
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Publikacje w roku 2014

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Artykuły w czasopismach z listy A MNiSW

[1] Acampora G., Pedrycz W., Vasilakos A.: Efficient modeling of MIMO systems through timed Automata based Neuro-Fuzzy Inference engine. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, vol. 55, No. 55, 2014, ss. 1336-1356, 35 poz. bibl.
[2] Alexander G., Wilbik A., Keller J., Musterman K.: Generating Sensor Data Summaries to Communicate Change in Elder's Health Status. APPLIED CLINICAL INFORMATICS, vol. 5, No. 1, 2014, ss. 73-84.
[3] Aliev R., Pedrycz W., Alizadeh A., Huseynov O.: Fuzzy optimality based decision making under imperfect information without utility. FUZZY OPTIMIZATION AND DECISION MAKING , vol. 12, No. 12, 2013 [druk w 2014 roku], ss. 357-372, 41 poz. bibl.
[4] Badica C., Ilie S., Muscar A., Badica A., Sandu L., Sbora R., Ganzha M., Paprzycki M.: Distributed Agent-Based Online Auction System. COMPUTING AND INFORMATICS, vol. 33, No. 3, 2014, ss. 518-552.
[5] Bednarczuk E., Syga M.: Minimax theorems for ?-convex functions with applications. CYBERNETICS AND SYSTEMS, vol. 43, No. 3, 2014, ss. 421-437.
[6] Bereta M., Pedrycz W., Reformat M.: Local descriptors and similarity measures for frontal face recognition: A comparative analysis. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, vol. 24, No. 24, 2013 [druk w 2014 roku], ss. 1213-1231, 81 poz. bibl.
[7] Branke J., Greco S., Słowiński R., Zielniewicz P.: Learning Value Functions in Interactive Evolutionary Multiobjective Optimization. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, vol. 19, No. 1, 2014, ss. 88-102.
[8] Caiafa C., Cichocki A.: Stable, Robust and Super Fast Reconstruction of Tensors Using Multi -Way Projections. IEEE TRANSACTIONS ON SIGNAL PROCESSING, vol. 63, No. 3, 2014, ss. 780-793.
[9] Cavalcanti M., Cavalcanti V., Lasiecka I., Nascimaento F.: Intrinsic decay rate estimates for the wave equation with competing viscoelastic and frictional dissipative effects. DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS (DCDS-B), vol. 19, No. 7, 2014, ss. 1987-2012.
[10] Cavalcanti M., Cavalcanti V., Nascimaento F., Lasiecka I., Rodrigues J.: Uniform decay rates for the energy of Timoshenko system with arbitrary speeds of propagation and localized nonlinear damping. ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND PHYSIK, vol. 65, No. 6, 2014, ss. 1189-1206.
[11] Chen L., Jin J., Zhang Y., Wang X., Cichocki A.: A survey of the dummy face and human face stimuli used in BCI paradigm. JOURNAL OF NEUROSCIENCE METHODS, vol. 239, No. 239, 2015 [druk w 2014 roku], ss. 18-27.
[12] Chueshov I., Lasiecka I., Webster J.: Attractors for delayed, nonrotational von Karman plates with applications to flow-structure interactions without any damping. COMMUNICATIONS IN PARTIAL DIFFERENTIAL EQUATIONS, vol. 39, No. 11, 2014, ss. 1965-1997.
[13] Cong F., Zhou G., Astikainen P., Zhao Q., Wu Q., Nandi A., Hietanen J., Ristaniemi T., Cichocki A.: Low-Rank Approximation based Non-Negative MultiWay Array Decomposition on Event-Related Potentials. INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, vol. 24, No. 8, 2014, ss. 1440005-1-1440005-19, 66 poz. bibl.
[14] Dmitruk A. .., Osmolovskii N.: Necessary Conditions for a weak Minimum in Optimal control problems with integral equations subject to state and mixed constraints. SIAM JOURNAL ON CONTROL AND OPTIMIZATION, vol. 52, No. 6, 2014, ss. 3437-3462.
[15] Evtushenko Y., Tretiakow A.: ρth-Order Numerical Methods for Solving Systems of Nonlinear Equations. DOKLADY MATHEMATICS, vol. 89, No. 2, 2014, ss. 214-217.
[16] Fantke P., Jolliet O., Evans J., Apte J., Cohen A., Hänninen O., Hurley F., Jantunen M., Jerrett M., Levy J., Loh M., Marshall J., Tainio M.: Health effects of fine particulate matter in life cycle impact assessment: findings from the Basel Guidance Workshop. INTERNATIONAL JOURNAL OF LIFE CYCLE ASSESSMENT, No.  doi:10.10, 2014, ss. 1-13, 89 poz. bibl.
[17] Ganghoffer J., Plotnikov P., Sokołowski J.: Mathematical modeling of volumetric material growth. ARCHIVE OF APPLIED MECHANICS, vol. 84, 2014, ss. 1357-1371.
[18] Ganghoffer J., Plotnikov P., Sokołowski J.: Mathematical Modeling of Volumetric Material Growth in Thermoelasticity. JOURNAL OF ELASTICITY , vol. 117, 2014, ss. 111-138.
[19] Ganghoffer J., Sokołowski J.: A micromechanical approach to volumetric and surface growth in the framework of shape optimization. INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE, vol. 74, 2014, ss. 207-226.
[20] Ganzha M., Paprzycki M.: Agent-Oriented Computing for Distributed Systems and Networks. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, vol. 37, 2014, ss. 45-46.
[21] Gągolewski M.: Spread measures and their relation to aggregation functions. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, vol. 241, No. 2, 2015 [druk w 2014 roku], ss. 469-477, 29 poz. bibl.
[22] Gągolewski M., Mesiar R.: Monotone measures and universal integrals in a uniform framework for the scientific impact assessment problem. INFORMATION SCIENCES, vol. 263, No. 1, 2014, ss. 166-174, 26 poz. bibl.
[23] Giusti S., Sokołowski J., Stebel J.: On Topological Derivatives for Contact Problems in Elasticity. JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, vol. 165, No. 1, 2014, ss. 279-294.
[24] Grzegorzewski P., Pasternak-Winiarska K.: Natural trapezoidal approximations of fuzzy numbers. FUZZY SETS AND SYSTEMS, vol. 250, 2014, ss. 90-109, 38 poz. bibl.
[25] Herrera-Viedma E., Cabrerizo F., Kacprzyk J., Pedrycz W.: A review of soft consensus models in a fuzzy environment. INFORMATION FUSION, vol. 17, 2014, ss. 4-13, 74 poz. bibl.
[26] Hryniewicz O., Karpiński J.: Prediction of reliability - the pitfalls of using Pearson's correlation. EKSPLOATACJA I NIEZAWODNOść - MAINTENANCE AND RELIABILITY, vol. 16, No. 3, 2014, ss. 472-483, 19 poz. bibl.
[27] Ignatova M., Kukavica I., Lasiecka I., Tuffaha A.: On well-posedness and small data global existence for an interface damped free boundary fluid-structure model. NONLINEARITY, vol. 27, No. 3, 2014, ss. 467-499.
[28] Isazadeh A., Pedrycz W., Mahan F.: ECA rule learning in dynamic environments. EXPERT SYSTEMS WITH APPLICATIONS, vol. 41, No. 41, 2014, ss. 7847-7857, 50 poz. bibl.
[29] Izakian H., Pedrycz W.: Agreement-based fuzzy C-means for clustering data with blocks of features. NEUROCOMPUTING, vol. 127, No. 127, 2014, ss. 266-280, 30 poz. bibl.
[30] Jin J., Allison B., Zhang Y., Wang X., Cichocki A.: An ERP-Based BCI using an Oddball Paradigm with different faced and reduced errors in critical functions. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, vol. 24, No. 8, 2014, ss. 1450027-1-1450027-14, 39 poz. bibl.
[31] Jonas M., Marland G., Krey V., Wagner F., Nahorski Z.: Uncertainty in an emission-constrained world. CLIMATIC CHANGE, vol. 124, No. 3, 2014, ss. 459-476, 32 poz. bibl.
[32] Kadziński M., Corrente S., Greco S., Słowiński R.: Preferential reducts and constructs in robust multiple criteria ranking and sorting. OR SPECTRUM, vol. 36, No. 4, 2014, ss. 1021-1053.
[33] Kadziński M., Greco S., Słowiński R.: Robust Ordinal Regression for Dominance-based Rough Set Approach to Multiple Criteria Sorting. INFORMATION SCIENCES, vol. 283, 2014, ss. 211-228.
[34] Kaliszewski I., Miroforidis J.: Two-sided Pareto Front Approximations. JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, vol. 162, 2014, ss. 845-855.
[35] Lasiecka I., Webster J.: Eliminating flutter for clamped von Karman plates immersed in subsonic flows. COMMUNICATIONS ON PURE AND APPLIED ANALYSIS, vol. 13, No. 5, 2014, ss. 1935-1969.
[36] Lasiecka I., Webster J.: Nonlinear plates interacting with a subsonic, inviscid flow via Kutta-Joukowski interface conditions. NONLINEAR ANALYSIS-REAL WORLD APPLICATIONS, vol. 17, 2014, ss. 171-191.
[37] Lesiv M., Bun A., Jonas M.: Analysis of change in relative uncertainty in GHG emissions from stationary sources for the EU 15. CLIMATIC CHANGE, vol. 124, No. 3, 2014, ss. 505-518, 22 poz. bibl.
[38] Leugering G., Sokołowski J., Żochowski A.: Control of Crack Propagation by Shape-Topological Optimization. DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS (DCDS-A), vol. 35, No. 6, 2015 [druk w 2014 roku], ss. 2625-2657.
[39] Lu W., Pedrycz W., Liu X., Yang J., Li P.: The modelling of time series based on fuzzy information granules. EXPERT SYSTEMS WITH APPLICATIONS, vol. 41, No. 41, 2014, ss. 3799-3808, 29 poz. bibl.
[40] Łukasik S., Kulczycki P.: An Algorithm for Reducing Dimension and Size of Sample for Data Exploration Procedures. INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE, vol. 24, No. 1, 2014, ss. 133-149, 54 poz. bibl.
[41] Medak B., Tretiakow A.: ρ-Regular Nonlinear Dynamics. DOKLADY MATHEMATICS, vol. 89, No. 1, 2014, ss. 112-114, 8 poz. bibl.
[42] Nahorski Z., Stańczak J., Pałka P.: Simulation of an uncertain emission market for greenhouse gases using agent-based methods. CLIMATIC CHANGE, vol. 124, No. 3, 2014, ss. 647-662, 23 poz. bibl.
[43] Nowak P., Romaniuk M.: Application of Levy processes and Esscher transformed martingale measures for option pricing in fuzzy framework. JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, vol. 263, 2014, ss. 129-151.
[44] Ometto J., Bun R., Jonas M., Nahorski Z., Gusti M.: Uncertainties in greenhouse gases inventories - expanding our perspective. CLIMATIC CHANGE, vol. 124, No. 3, 2014, ss. 451-458, 7 poz. bibl.
[45] Osmolovskii N.: On Second-Order Necessary Conditions for Broken Extremals. JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, vol. 162, No. 1, 2015 [druk w 2014 roku].
[46] OSullivan D., Wilk S., Michałowski W., Słowiński R., Thomas R., Kadziński M., Farion K.: Learning the preferences of physicians for the organization of result lists of medical documents. METHODS OF INFORMATION IN MEDICINE, vol. 53, No. 5, 2014, ss. 344-356.
[47] Pałkowski Ł., Błaszczyński J., Skrzypczak A., Błaszczak J., Kozakowska K., Wróblewska J., Kożuszko S., Gospodarek E., Krysiński J., Słowiński R.: Antimicrobial Activity and SAR Study of New Gemini Imidazolium-based Chlorides. CHEMICAL BIOLOGY & DRUG DESIGN, vol. 83, No. 3, 2014, ss. 278-288.
[48] Pałkowski Ł., Krysiński J., Błaszczyński J., Słowiński R., Skrzypczak A., Błaszczak J., Gospodarek E., Wróblewska J.: Application of Rough Set Theory to Prediction of Antimicrobial Activity of Bis-Quaternary Imidazolium Chlorides. FUNDAMENTA INFORMATICAE, vol. 132, 2014, ss. 315-330.
[49] Park J., Jeon M., Pedrycz W.: Spectral clustering with physical intuition on spring-mass dynamics. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, vol. 351, No. 351, 2014, ss. 3245-3268, 40 poz. bibl.
[50] Pawłow-Niezgódka I., Zajączkowski W.: The global solvability of a sixth order Cahn--Hilliard type equation via the Backlund transformation. COMMUNICATIONS ON PURE AND APPLIED ANALYSIS, vol. 13, No. 2, 2014, ss. 859-880, 23 poz. bibl.
[51] Pedrycz W.: From Numeric to Granular Description and Interpretation of Information Granules. FUNDAMENTA INFORMATICAE, vol. 127, No. 1-4, 2013 [druk w 2014 roku], ss. 399-412, 15 poz. bibl.
[52] Pedrycz W., Song M.: A granulation of linguistic information in AHP decision-making problems. INFORMATION FUSION, vol. 17, No. 17, 2014, ss. 93-101, 23 poz. bibl.
[53] Prusińska A., Szczepanik E., Tretiakow A.: High-order optimality conditions for degenerate variational problems. CARPATHIAN JOURNAL OF MATHEMATICS, vol. 30, No. 3, 2014, ss. 387-394.
[54] Rojek I., Studziński J.: Comparison of different types of neuronal nets for failures location within water supply networks. EKSPLOATACJA I NIEZAWODNOść - MAINTENANCE AND RELIABILITY, vol. 16, No. 1, 2014, ss. 42-47, 16 poz. bibl.
[55] See L., Schepaschenko D., Lesiv M., McCallum I., Fritz S.: Building a hybrid land cover map with crowdsourcing and geographically weighted regression. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, vol. 103, No. 10.1016/j., 2014, ss. 48-56, 41 poz. bibl.
[56] Stachura M., Studziński J.: Prognozowanie obciązenia hydraulicznego miejskiego systemu wodociągowego z wykorzystaniem modeli rozmytych typu TSK. OCHRONA ŚRODOWISKA, vol. 36, No. 1, 2014, ss. 57-60, 12 poz. bibl.
[57] Susmaga R., Słowiński R.: Generation of rough set reduct and constructs based on inter-class and intra-class information. FUZZY SETS AND SYSTEMS, 2014, ss. 1-19.
[58] Szeląg M., Greco S., Słowiński R.: Variable consistency dominance-based rough set approach to preference learning in multicriteria ranking. INFORMATION SCIENCES, vol. 277, 2014, ss. 525-552.
[59] Szulc K., Żochowski A.: Application of topological derivative to accelerate genetic algorithm in shape optimization of coupled models. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, vol. 51, No. 1, 2014, ss. 183-192, 1 poz. bibl.
[60] Szymczak M., Zadrożny S., Bronselaer A., De Tre G.: Coreference detection in an XML schema. INFORMATION SCIENCES, vol. 296, 2015 [druk w 2014 roku], ss. 237-262.
[61] Świechowski M., Mańdziuk J.: Self-Adaptation of Playing Strategies in General Game Playing. IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES, vol. 6, No. 4, 2014, ss. 367-381.
[62] Tainio M., Holnicki-Szulc P., Loh M., Nahorski Z.: Intake Fraction Variability Between Air Pollution Emission Sources Inside an Urban Area. RISK ANALYSIS, vol. 34, No. 11, 2014, ss. 2021-2034, 36 poz. bibl.
[63] Tainio M., Olkowicz D., Teresinski G., de Nazelle A., Nieuwenhuijsen M.: Severity of injuries in different modes of transport, expressed with disability-adjusted life years (DALYs). BMC PUBLIC HEALTH, vol. 14, No. 765, 2014, ss. 1-10, 34 poz. bibl.
[64] Tomita Y., Vialatte F., Dreyfus G., Mitsukura Y., Bakardjian H., Cichocki A.: Bimodal BCI Using Simultaneously NIRS and EEG. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, vol. 61, No. 4, 2014, ss. 1274-1284, 38 poz. bibl.
[65] Tretiakow A., Szczepanik E.: Irregular Optimization Models and ρ-Order Kuhn-Tucker Optimality Conditions. JOURNAL OF COMPUTER AND SYSTEM SCIENCES INTERNATIONAL, vol. 53, No. 3, 2014, ss. 384-391.
[66] Verstraete J.: Solving the map overlay problem with a fuzzy approach. CLIMATIC CHANGE, vol. 124, No. 3, 2014, ss. 591-604, 15 poz. bibl.
[67] Wasielewska K., Ganzha M., Paprzycki M., Szmeja P., Drozdowicz M., Lirkov I., Badica C.: Applying Saaty's Multicriterial Decision Making Approach in Grid Resource Management. INFORMATION TECHNOLOGY AND CONTROL, vol. 43, No. 1, 2014, ss. 73-87.
[68] Wilbik A., Keller J., Bezdek J.: Linguistic Prototypes for Data From Eldercare Residents. IEEE TRANSACTIONS ON FUZZY SYSTEMS, vol. 22, No. 1, 2014, ss. 110-123, 40 poz. bibl.
[69] Woodcock J., Tainio M., Chesire J., OBrien O., Goodman A.: Health effects of the London bicycle sharing system: health impact modelling study. BRITISH MEDICAL JOURNAL, vol. 348, No. g425, 2014, ss. 1-14, 55 poz. bibl.
[70] Wu Q., Zhang L., Cichocki A.: Multifactor sparse feature extraction using Convolutive Nonnegative Tucker Decomposition. NEUROCOMPUTING, vol. 129, 2014, ss. 17-24.
[71] Xu X., Horabik J., Nahorski Z.: Pricing of uncertain certified emission reductions in a Chinese coal mine methane project with an extended Rubinstein-Ståhl model. CLIMATIC CHANGE, vol. 124, 2014, ss. 617-632, 23 poz. bibl.
[72] Yu J., Jeon M., Pedrycz W.: Weighted feature trajectories and concatenated bag-of-features for action recognition. NEUROCOMPUTING, vol. 131, No. 131, 2014, ss. 200-207, 41 poz. bibl.
[73] Yu Y., Pedrycz W., Miao D.: Multi-label classification by exploiting label correlations. EXPERT SYSTEMS WITH APPLICATIONS, vol. 41, No. 41, 2014, ss. 2989-3004, 31 poz. bibl.
[74] Zhang Y., Zhou G., Jin J., Wang X., Cichocki A.: Frequency Recognition in SSVEP-Based BCI Using Multiset Canonical Correlation Analysis. INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, vol. 24, No. 3, 2014, ss. 1450013-1-1450013-14, 58 poz. bibl.
[75] Zhang Y., Zhou G., Jin J., Wang X., Cichocki A.: SSVEP recognition using common feature analysis in brain-computer. JOURNAL OF NEUROSCIENCE METHODS, vol. 244, 2015 [druk w 2014 roku], ss. 8-15.
[76] Zhao Q., Zhang L., Cichocki A.: Multilinear and nonlinear generalizations of partial least squares: an overview of recent advances. DATA MINING AND KNOWLEDGE DISCOVERY, vol. 4, No. 2, 2014, ss. 104-115, 59 poz. bibl.
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 Z wielką radością informujemy, że nasz znakomity Kolega prof. dr. hab. inż. Janusz Kacprzyk otrzymał tytul doktora honoris causa  w Laapeenranta University of Technology, Laapeenranta, Finlandia. Wsród 14 laureatow są wybitni naukowcy, liderzy biznesu, technologii, mediow, polityki itp. Więcej informacji można znaleźć tutaj i tutaj.   Serdecznie...czytaj dalej »

Z radością przyjęlismy wiadomość, że Profesor Janusz Kacprzyk otrzymał kolejne wyróżnienie: 2016 Individual Award for Outstanding Contributions in the field of Computational Intelligence nadane przez Oddział Indyjski International Neural Network Society (INNS Indian Chapter).   INNS jest prestiżowym światowym towarzystwem naukowym, a jego oddzial w...czytaj dalej »


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