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    Tytuł:
    Research on SDG fault diagnosis of ocean shipping boiler system based on fuzzy granular computing under data fusion
    Autorzy:
    Zhu, Y.
    Geng, L.
    Powiązania:
    https://bibliotekanauki.pl/articles/258772.pdf
    Data publikacji:
    2018
    Wydawca:
    Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
    Tematy:
    granular computing
    symbolic digraph
    fault diagnosis
    fuzzy theory
    Opis:
    The research work in this paper belongs to the application of granular computing, graph theory and its application in fault detection and diagnosis. It is a cross cutting and frontier research field in computer science, information science and graph theory. The results of this paper are of great significance to the application of the fault detection and diagnosis of the ocean boilers system. This research combines granular computing theory and signed directed graph, and proposes a new method of fault diagnosis, and applies it to the fault diagnosis of ocean ship boiler system.
    Źródło:
    Polish Maritime Research; 2018, S 2; 92-97
    1233-2585
    Pojawia się w:
    Polish Maritime Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Computing with words with the use of inverse RDM models of membership functions
    Autorzy:
    Piegat, A.
    Pluciński, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/330406.pdf
    Data publikacji:
    2015
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    computing with words
    fuzzy arithmetic
    RDM fuzzy arithmetic
    granular computing
    Opis:
    Computing with words is a way to artificial, human-like thinking. The paper shows some new possibilities of solving difficult problems of computing with words which are offered by relative-distance-measure RDM models of fuzzy membership functions. Such models are based on RDM interval arithmetic. The way of calculation with words was shown using a specific problem of flight delay formulated by Lotfi Zadeh. The problem seems easy at first sight, but according to the authors’ knowledge it has not been solved yet. Results produced with the achieved solution were tested. The investigations also showed that computing with words sometimes offers possibilities of achieving better problem solutions than with the human mind.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2015, 25, 3; 675-688
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Communication among agents: a set theoretic approach
    Autorzy:
    Mousavi, Amin
    Jabedar-Maralani, Parviz
    Powiązania:
    https://bibliotekanauki.pl/articles/2012710.pdf
    Data publikacji:
    2003
    Wydawca:
    Politechnika Gdańska
    Tematy:
    computing with words
    granular computing
    fuzzy sets
    rough sets
    multi-valued logic
    Opis:
    This paper uses the notion of relative sets in relation to fuzzy set theory to provide a mathematical framework to analyze communication among agents. Each relative set partitions all objects into four distinct regions corresponding to four truth-values of Belnap’s logic. Two orderings on relative sets are considered; one is an extension of the classical set inclusion ordering while the other is a new ordering of knowledge or information. According to these orderings, we can divide set theoretic problems into two major categories: reasoning problems and communicating problems. In the first category, an agent tries to extract a sound decision through granular reasoning. In this case, a granule represents a concept or a word. In the second category, each granule relates to an agent, and the problem is to compare agents’ knowledge about concepts by their related granules, e.g. a knowledge reduction problem. Then, we concentrate on the second category of problems and try to investigate this kind of problems in the context of fuzzy set theory. In this way, we could provide a basis for modeling and analyzing the relations among machines, which could communicate with each other using words and granules.
    Źródło:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2003, 7, 1; 53-64
    1428-6394
    Pojawia się w:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    GrDBSCAN: A granular density-based clustering algorithm
    Autorzy:
    Suchy, Dawid
    Siminski, Krzysztof
    Powiązania:
    https://bibliotekanauki.pl/articles/15548018.pdf
    Data publikacji:
    2023
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    granular computing
    DBSCAN
    clustering algorithm
    GrDBSCAN
    przetwarzanie ziarniste
    algorytm grupowania
    Opis:
    Density-based spatial clustering of applications with noise (DBSCAN) is a commonly known and used algorithm for data clustering. It applies a density-based approach and can produce clusters of any shape. However, it has a drawback-its worst-case computational complexity is O(n2) with regard to the number of data items n. The paper presents GrDBSCAN: a granular modification of DBSCAN with reduced complexity. The proposed GrDBSCAN first granulates data into fuzzy granules and then runs density-based clustering on the resulting granules. The complexity of GrDBSCAN is linear with regard to the input data size and higher only for the number of granules. That number is, however, a parameter of the GrDBSCAN algorithm and is (significantly) lower than that of input data items. This results in shorter clustering time than in the case of DBSCAN. The paper is accompanied by numerical experiments. The implementation of GrDBSCAN is freely available from a public repository.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2023, 33, 2; 297--312
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Relations of granular worlds
    Autorzy:
    Pedrycz, W.
    Vukovich, G.
    Powiązania:
    https://bibliotekanauki.pl/articles/908015.pdf
    Data publikacji:
    2002
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    elektrotechnika
    granular computing
    clustering
    models of collaborative computing
    fuzzy models
    collaboration and competition
    FCM
    granular modeling
    Opis:
    In this study, we are concerned with a two-objective development of information granules completed on a basis of numeric data. The first goal of this design concerns revealing and representing a structure in a data set. As such it is very much oriented towards coping with the underlying relational aspects of the experimental data. The second goal deals with a formation of a mapping between information granules constructed in two spaces (thus it concentrates on the directional aspect of information granulation). The quality of the mapping is directly affected by the information granules over which it operates, so in essence we are interested in the granules that not only reflect the data but also contribute to the performance of such a mapping. The optimization of information granules is realized through a collaboration occurring at the level of the data and the mapping between the data sets. The operational facet of the problem is cast in the realm of fuzzy clustering. As the standard techniques of fuzzy clustering (including a well-known approach of FCM) are aimed exclusively at the first objective identified above, we augment them in order to accomplish sound mapping properties between the granules. This leads to a generalized version of the FCM (and any other clustering technique for this matter). We propose a generalized version of the objective function that includes an additional collaboration component to make the formed information granules in rapport with the mapping requirements (that comes with a directional component captured by the information granules). The additive form of the objective function with a modifiable component of collaborative activities makes it possible to express a suitable level of collaboration and to avoid a phenomenon of potential competition in the case of incompatible structures and the associated mapping. The logic-based type of the mapping (that invokes the use of fuzzy relational equations) comes ...
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2002, 12, 3; 347-357
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    GrNFS: A granular neuro-fuzzy system for regression in large volume data
    Autorzy:
    Siminski, Krzysztof
    Powiązania:
    https://bibliotekanauki.pl/articles/2055169.pdf
    Data publikacji:
    2021
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    granular computing
    neuro-fuzzy system
    large volume data
    machine learning
    przetwarzanie ziarniste
    system neurorozmyty
    uczenie maszynowe
    Opis:
    Neuro-fuzzy systems have proved their ability to elaborate intelligible nonlinear models for presented data. However, their bottleneck is the volume of data. They have to read all data in order to produce a model. We apply the granular approach and propose a granular neuro-fuzzy system for large volume data. In our method the data are read by parts and granulated. In the next stage the fuzzy model is produced not on data but on granules. In the paper we introduce a novel type of granules: a fuzzy rule. In our system granules are represented by both regular data items and fuzzy rules. Fuzzy rules are a kind of data summaries. The experiments show that the proposed granular neuro-fuzzy system can produce intelligible models even for large volume datasets. The system outperforms the sampling techniques for large volume datasets.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2021, 31, 3; 445--459
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Toward interactive rough-granular computing
    Autorzy:
    Skowron, A.
    Wasilewski, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/206358.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    rough sets
    granular computing
    interactive computations
    perception based computing
    perception attributes
    sensory attributes
    action attributes
    vague concepts
    approximation of complex vague concepts
    ontology approximation
    Opis:
    Computations in Rough-Granular Computing (RGC) are performed on (information) granules. The rough set approach is used in RGC for inducing granules approximating other granules about which imperfect knowledge is given only. For modeling of complex systems, it is important to extend the RGC approach to Interactive Rough-Granular Computing (IRGC) based on interactions of granules. In this paper, we discuss some fundamental issues for interaction of granules such as general scheme of interactions and the role of dynamic attributes and dynamic information systems in modeling interactive computations.
    Źródło:
    Control and Cybernetics; 2011, 40, 2; 213-235
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Granular representation of the information potentialof variables –application example
    Ziarnista reprezentacja potencjału informacyjnego zmiennych –przykład zastosowania
    Autorzy:
    Kiersztyn, Adam
    Gandzel, Agnieszka
    Celiński, Maciej
    Koczan, Leopold
    Powiązania:
    https://bibliotekanauki.pl/articles/2070228.pdf
    Data publikacji:
    2021
    Wydawca:
    Politechnika Lubelska. Wydawnictwo Politechniki Lubelskiej
    Tematy:
    granular computing
    information granules
    knowledge representation
    fuzzy clustering
    ecological data
    obliczenia ziarniste
    ziarna informacji
    reprezentacja wiedzy
    grupowanie rozmyte
    dane ekologiczne
    Opis:
    With the introduction to the science paradigm of Granular Computing, in particular, information granules, the way of thinking about data has changed gradually. Both specialists and scientists stopped focusing on the single data records themselves, but began to look at the analyzed data in a broader context, closer to the way people think. This kind of knowledge representation is expressed, in particular, in approaches based on linguistic modelling or fuzzy techniques such as fuzzy clustering. Therefore, especially important from the point of view of the methodology of data research, is an attempt to understand their potential as information granules. In this study, we will present special cases of using the innovative method of representing the information potential of variables with the use of information granules. In a series of numerical experiments based on both artificially generated data and ecological data on changes in bird arrival dates in the context of climate change, we demonstrate the effectiveness of the proposed approach using classic, not fuzzy measures building information granules.
    Wraz z wprowadzeniem do nauki paradygmatu obliczeń ziarnistych, w szczególności ziaren informacji, sposób myślenia o danych stopniowo się zmieniał. Zarówno specjaliści, jak i naukowcy przestali skupiać się na samych rekordach pojedynczych danych, ale zaczęli patrzeć na analizowane dane w szerszym kontekście, bliższym ludzkiemu myśleniu. Ten rodzaj reprezentacji wiedzy wyraża się w szczególności w podejściach opartych na modelowaniu językowym lub technikach rozmytych, takich jak klasteryzacja rozmyta. Dlatego szczególnie ważna z punktu widzenia metodologii badania danych jest próba zrozumienia ich potencjału jako ziaren informacji. W niniejszym opracowaniu przedstawimy szczególne przypadki wykorzystania innowacyjnej metody reprezentacji potencjału informacyjnego zmiennych za pomocą ziaren informacji. W serii eksperymentów numerycznych opartych zarówno na danych generowanych sztucznie, jak i danych ekologicznych dotyczących zmian dat przylotów ptaków w kontekście zmian klimatycznych, demonstrujemy skuteczność proponowanego podejścia przy użyciu klasycznych, a nie rozmytych miar budujących ziarna informacji.
    Źródło:
    Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska; 2021, 11, 3; 40--44
    2083-0157
    2391-6761
    Pojawia się w:
    Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Models of computational intelligence in bioinformatics
    Autorzy:
    Pedrycz, W.
    Powiązania:
    https://bibliotekanauki.pl/articles/333235.pdf
    Data publikacji:
    2003
    Wydawca:
    Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
    Tematy:
    obliczenia granularne
    logika
    bioinformatyka
    granulki informacji
    zbiory rozmyte
    zbiory przybliżone
    granular computing
    logics
    bioinformatics
    information granules
    fuzzy sets
    rough sets
    Opis:
    Computational Intelligence has emerged as a synergistic environment of Granular Computing (including fuzzy sets, rough sets, interval analysis), neural networks and evolutionary optimisation. This symbiotic framework addresses the needs of system modelling with regard to its transparency, accuracy and user friendliness. This becomes of paramount interest in various modelling in bioinformatics especially when we are concerned with decision-making processes. The objective of this study is to elaborate on the two essential features of CI that is Granular Computing and the resulting aspects of logic-oriented processing and its transparency. As the name stipulates, Granular Computing is concerned with processing carried out at a level of coherent conceptual entities - information granules. Such granules are viewed as inherently conceptual entities formed at some level of abstraction whose processing is rooted in the language of logic (especially, many valued or fuzzy logic). The logic facet of processing is cast in the realm of fuzzy logic and fuzzy sets that construct a consistent processing background necessary for operating on information granules. Several main categories of logic processing units (logic neurons) are discussed that support aggregative (and-like and or-like operators) and referential logic mechanisms (dominance, inclusion, and matching). We show how the logic neurons contribute to high functional transparency of granular processing, help capture prior domain knowledge and give rise to a diversity of the resulting models.
    Źródło:
    Journal of Medical Informatics & Technologies; 2003, 5; IP13-23
    1642-6037
    Pojawia się w:
    Journal of Medical Informatics & Technologies
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    ANN as justified granular computing mechanism for medical data classification
    Autorzy:
    Bernas, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/333728.pdf
    Data publikacji:
    2015
    Wydawca:
    Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
    Tematy:
    artificial neural network
    granular computing
    data fusion
    medical data analysis
    sztuczne sieci neuronowe
    obliczenia ziarniste
    fuzja danych
    analiza danych medycznych
    Opis:
    The medical data and its classification have to be treated in particular way. The data should not be modified or altered, because this could lead to false decisions. Most state-of-the-art classifiers are using random factors to produce higher overall accuracy of diagnosis, however the stability of classification can vary significantly. Medical support systems should be trustworthy and reliable, therefore this paper proposes fusion of multiple classifiers based on artificial Neural Network (ANN). The structure selection of ANN is performed using granular paradigm, where granulation level is defined by ANN complexity. The classification results are merged using voting procedure. Accuracy of the proposed solution was compared with state-of-the-art classifiers using real medical data coming from two medical datasets. Finally, some remarks and further research directions have been discussed.
    Źródło:
    Journal of Medical Informatics & Technologies; 2015, 24; 85-90
    1642-6037
    Pojawia się w:
    Journal of Medical Informatics & Technologies
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fuzzy number division and the multi-granularity phenomenon
    Autorzy:
    Piegat, A.
    Pluciński, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/202398.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    granular computing
    fuzzy arithmetic
    fuzzy calculations
    RDM fuzzy arithmetic
    horizontal membership function
    przetwarzanie ziarniste
    arytmetyka liczb rozmytych
    RDM
    funkcja przynależności poziomej
    Opis:
    The paper presents difficulties connected with fuzzy and interval division. If operations such as fuzzy addition, subtraction and multiplication provide as a result one compact, multidimensional granule, then a result of the fuzzy division can consists of few separated granules. Such results are more difficult to use in next calculations. The paper shows that the number of solution granules can be higher than 2 and that in certain problems division does not occur explicitly. In certain problems, separation of particular solution granules can be considerable. The paper also shows how to realize the fuzzy division when its denominator contains zero. Most types of fuzzy arithmetics forbid such operation. However, the paper shows that it is possible. Multidimensional fuzzy RDM arithmetic and horizontal membership functions which facilitate detecting of solution granules are also described. The considered problems are visualized by examples.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2017, 65, 4; 497-511
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Digital camera as a data source of ITS solutions in traffic control and management
    Kamera cyfrowa jako źródło danych koncepcji ITS dla sterowania i zarządzania ruchem drogowym
    Autorzy:
    Piecha, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/374445.pdf
    Data publikacji:
    2012
    Wydawca:
    Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
    Tematy:
    detekcja ruchu wideo
    modelowanie ruchu
    obliczenia granularne
    automaty komórkowe
    pojazdy manewrowe
    traffic video detection
    road traffic modelling
    granular computing
    cellular automata
    vehicles manoeuvres
    Opis:
    The traffic adaptive-control processes and Intelligent Transportation Systems (ITS) work on traffic characteristics provided by vehicles various detectors. In majority cases the algorithms work on vehicles number evidences only, recorded on traffic lanes. The expected data concerns the vehicles number and a time schedule observed at stop-lines on intersection inlets or another points of the traffic intensity checking. A satisfactory usage of the video technology needs various simplifications of the data source structure and the processing algorithms. For simplification of these all processes several solutions must be implemented. One can try reducing the data size and improve the processing algorithms. Better results can be expected after proper selection of the data sampling intervals, namely the data granularity finding. Several conclusions concerning the traffic recording and modeling are presented in this work. The discussed technology was implemented to produce.
    Adaptacyjne sterowanie procesem transportowym oraz tzw. Inteligentne Systemy Transportowe (ITS) korzystają z charakterystycznych danych zarejestrowanych za pomocą różnych detektorów ruchu. W większości przypadków algorytmy sterowania wykorzystują zapis o liczbie pojazdów na pasach ruchu. Potrzebne dane dotyczą zarówno liczby pojazdów, jak i czasów ich dojazdu do linii zatrzymania na wlocie skrzyżowania lub innego charakterystycznego punktu pomiaru natężenia ruchu. Zadowalające zastosowanie technik pomiarowych wideo uwarunkowane jest wprowadzeniem wielu uproszczeń dla rejestrowanych danych i algorytmów przetwarzania. Modelowanie strumieni pojazdów wiąże się zwykle z pewnymi stratami rejestrowanych danych. Często te dane są nadmiarowe dla uzyskania zadowalającej jakości sterowania ruchem. Dla uproszczenia wszystkich faz sterowania przedstawiono kilka ważnych rozwiązań z teorii rejestracji i przetwarzania danych. Można dokonać znaczącej redukcji rozmiaru plików danych wejściowych oraz uprościć algorytmy ich przetwarzania, nie tracąc niczego z jakości sterowania. Dobrym sposobem dla tych ograniczeń jest określenie właściwego interwału próbkowania danych pomiarowych oraz zdefiniowanie rozmiarów ziarna pomiarowego systemu sterowania. Kilka istotnych rozwiązań, dotyczących rejestracji i modelowania procesów transportowych, zaprezentowano w niniejszym artykule. Opracowania te zostały wdrożone do produkcji.
    Źródło:
    Transport Problems; 2012, 7, 4; 57-70
    1896-0596
    2300-861X
    Pojawia się w:
    Transport Problems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The approach of granular computing and rough sets for identifying situations
    Autorzy:
    Burov, Ye.
    Mykich, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/411410.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Oddział w Lublinie PAN
    Tematy:
    situation
    situational awareness system
    ontology
    situational assessment
    granular computing
    rough sets theory
    koniunktura
    system świadomości sytuacji
    ontologia
    ocena sytuacji
    obliczenia ziarniste
    teoria zbiorów przybliżonych
    Opis:
    In the article are described problems related to creation and maintenance of situational awareness systems. The definitions of concepts of situation and its identification are presented. An approach based on situational knowledge representation with ontological models is selected for attaining situational awareness in complex intelligent enterprise systems, where objects can be in several situations in the same time and some situations are defined imprecisely. Granular computing approach is used for reduction of situational knowledge management complexity. In order to work with situation defined imprecisely, rough set approximations are proposed for situation definition. The usage of mechanisms inherent to ontological modeling for situation representation and reasoning about them are also discussed.
    Źródło:
    ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes; 2017, 6, 2; 45-50
    2084-5715
    Pojawia się w:
    ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    New frontiers of analysis, interpretation and classification of biomedical signals: a computational intelligence framework
    Autorzy:
    Gacek, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/333497.pdf
    Data publikacji:
    2011
    Wydawca:
    Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
    Tematy:
    sygnał EKG
    inteligencja obliczeniowa
    zbiory rozmyte
    granulki informacji
    ziarnista informatyka
    interpretacja
    klasyfikacja
    współdziałanie
    ECG signals
    computational intelligence
    neurocomputing
    fuzzy sets
    information granules
    granular computing
    interpretation
    classification
    interpretability
    Opis:
    The methods of Computational Intelligence (CI) including a framework of Granular Computing, open promising research avenues in the realm of processing, analysis and interpretation of biomedical signals. Similarly, they augment the existing plethora of "classic" techniques of signal processing. CI comes as a highly synergistic environment in which learning abilities, knowledge representation, and global optimization mechanisms and this essential feature is of paramount interest when processing biomedical signals. We discuss the main technologies of Computational Intelligence (namely, neural networks, fuzzy sets, and evolutionary optimization), identify their focal points and elaborate on possible limitations, and stress an overall synergistic character, which ultimately gives rise to the highly symbiotic CI environment. The direct impact of the CI technology on ECG signal processing and classification is studied with a discussion on the main directions present in the literature. The design of information granules is elaborated on; their design realized on a basis of numeric data as well as pieces of domain knowledge is considered. Examples of the CI-based ECG signal processing problems are presented. We show how the concepts and algorithms of CI augment the existing classification methods used so far in the domain of ECG signal processing. A detailed construction of granular prototypes of ECG signals being more in rapport with the diversity of signals analyzed is discussed as well. ECG signals, Computational Intelligence, neurocomputing, fuzzy sets, information granules, Granular Computing, interpretation, classification, interpretability.
    Źródło:
    Journal of Medical Informatics & Technologies; 2011, 17; 23-36
    1642-6037
    Pojawia się w:
    Journal of Medical Informatics & Technologies
    Dostawca treści:
    Biblioteka Nauki
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