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    Wyświetlanie 1-11 z 11
    Tytuł:
    Real-time interpolation of streaming data
    Autorzy:
    Dębski, Roman
    Powiązania:
    https://bibliotekanauki.pl/articles/1839246.pdf
    Data publikacji:
    2020
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    streaming algorithm
    online algorithm
    spline interpolation
    cubic Hermite spline
    Opis:
    One of the key elements of the real-time C 1 -continuous cubic spline interpolation of streaming data is an estimator of the first derivative of the interpolated function that is more accurate than those based on finite difference schemas. Two such greedy look-ahead heuristic estimators, based on the calculus of variations (denoted as MinBE and MinAJ2), are formally defined (in closed form), along with the corresponding cubic splines that they generate. They are then comparatively evaluated in a series of numerical experiments involving different types of performance measures. The presented results show that the cubic Hermite splines generated by heuristic MinAJ2 significantly outperformed those that were based on finite difference schemas in terms of all of the tested performance measures (including convergence). The proposed approach is quite general. It can be directly applied to streams of univariate functional data like time-series. Multi-dimensional curves that are defined parametrically (after splitting) can be handled as well. The streaming character of the algorithm means that it can also be useful in processing data sets that are too large to fit in the memory (e.g., edge computing devices, embedded time-series databases).
    Źródło:
    Computer Science; 2020, 21 (4); 513-532
    1508-2806
    2300-7036
    Pojawia się w:
    Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The look-up algorithm of monitoring an object described by non-linear ordinary differential equations
    Autorzy:
    Hawro, Przemysław
    Kwater, Tadeusz
    Bartman, Jacek
    Kwiatkowski, Bogdan
    Powiązania:
    https://bibliotekanauki.pl/articles/2204529.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    adaptive estimation
    polluted river
    MATLAB
    lookup algorithm
    monitoring online
    algorytm wyszukiwania
    monitorowanie on-line
    zanieczyszczenie rzeki
    szacowanie adaptacyjne
    Opis:
    The article proposes an adaptive algorithm that generates all object signals, including those for which measurements are not performed due to the difficulties associated with on-line measurements. The algorithm is modeled on the idea of the Kalman filter using its equation, however, the selection of gains is optimized in a different way, i.e. the constant values depend on the adopted ranges of adaptation errors. Moreover, the knowledge of the statistics of all noise signals is not imposed and there is no linearity constraint. This approach allowed to reduce the complexity of calculations. This algorithm can be used in real-time systems to generate signals of objects described by non-linear differential equations and it is universal, which allows it to be used for various objects. In the conducted research, on the example of a biochemically contaminated river, only easily measurable signals were used to generated the object signals, and in addition, in the case of absence some measurements, the functioning of the algorithm did not destabilize.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 2; art. no. e144603
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Using Inconsistency Reduction Algorithms in Comparison Matrices to Improve the Performance of Generating Random Comparison Matrices with a Given Inconsistency Coefficient Range
    Autorzy:
    Kuraś, Paweł
    Gerka, Alicja
    Powiązania:
    https://bibliotekanauki.pl/articles/2201885.pdf
    Data publikacji:
    2023
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    algorithm
    pairwise comparison
    inconsistency ratio
    online tools
    Opis:
    The aim of this paper is to present a new method for generating random pairwise comparison matrices with a given inconsistency ratio (CR) interval using inconsistency reduction algorithms. Pairwise comparison (PC) is a popular technique for multi-criteria decision-making, its purpose is to assign weights to the compared entities, thus ranking them from best to worst. The presented method combines the traditional random generation of comparison matrices supported by inconsistency reduction algorithms: the “Xu and Wei” algorithm and the “Szybowski” algorithm. This paper presents research that shows an increase in performance when generating such matrices relative to the standard random comparison matrix generation procedure using the “Szybowski” algorithm. The other algorithms also improve the process, but to a lesser extent, making the “Szybowski” supporting algorithm the preferred solution for the new process. As a result of the research, a free online tool “PC MATRICES GENERATOR” has also been made available to efficiently generate a large number of comparison matrices with a given CR factor range, any matrix size, and any number of matrices, enabling much more efficient and less time-consuming research in many fields that use comparison matrices, as the analytic hierarchy/network process (AHP/ANP), ELECTREE, PAPRIKA, PROMETHE, VIKOR or the Best-Worst method (BWM).
    Źródło:
    Advances in Science and Technology. Research Journal; 2023, 17, 1; 222-229
    2299-8624
    Pojawia się w:
    Advances in Science and Technology. Research Journal
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Clothing Image Classification with a Dragonfly Algorithm Optimised Online Sequential Extreme Learning Machine
    Klasyfikacja obrazu odzieży za pomocą zoptymalizowanego algorytmu Dragonfly sekwencyjnej maszyny uczącej się
    Autorzy:
    Li, Jianqiang
    Shi, Weimin
    Yang, Donghe
    Powiązania:
    https://bibliotekanauki.pl/articles/1419412.pdf
    Data publikacji:
    2021
    Wydawca:
    Sieć Badawcza Łukasiewicz - Instytut Biopolimerów i Włókien Chemicznych
    Tematy:
    Dragonfly algorithm
    Online Sequential Extreme Learning Machine
    clothing image classification
    optimised parameter
    algorytm Dragonfly
    OSELM
    maszyna ucząca się
    klasyfikacja obrazu odzieży
    parametr zoptymalizowany
    Opis:
    This study proposes a solution for the issue of the low classification accuracy of clothing images. Using Fashion-MNIST as the clothing image dataset, we propose a clothing image classification technology based on an online sequential extreme learning machine (OSELM) optimised by the dragonfly algorithm (DA). First, we transform the Fashion-MNIST dataset into a data set that we extract from the corresponding grey image. Then, considering that the input weight and hidden layer bias of an OSELM are generated randomly, a DA is proposed to optimise the input weight and hidden layer bias of the OSELM to reduce the influence of random generation on the classification results. Finally, the optimised OSELM is applied to the clothing image classification. Compared to the other seven types of classification algorithms, the proposed clothing image classification model with the DA-optimised OSELM reached 93.98% accuracy when it contained 350 hidden nodes. Its performance was superior to other algorithms that were configured with the same number of hidden nodes. From a stability analysis of the box-plot, it was found that there were no outliers exhibited by the DA-OSELM model, whereas some other models had outliers or had lower stability compared to the model proposed, thereby validating the efficacy of the solution proposed.
    W pracy zaproponowano rozwiązanie problemu niskiej dokładności klasyfikacyjnej obrazów odzieży. Wykorzystując Fashion-MNIST jako zbiór danych obrazu odzieży, zaproponowano technologię klasyfikacji obrazów odzieży w oparciu o sekwencyjną maszynę uczącą się (OSELM) zoptymalizowaną przez algorytm Dragonfly (DA). Najpierw przekształcono zbiór danych Fashion-MNIST w zestaw danych, który wyodrębniono z obrazu. Następnie, biorąc pod uwagę, że waga wejściowa i odchylenie warstwy ukrytej OSELM były generowane losowo, w celu zmniejszenia wpływu generowania losowego na wyniki klasyfikacji zaproponowano DA w celu optymalizacji wagi wejściowej i obciążenia warstwy ukrytej OSELM. Następnie, zoptymalizowany OSELM zastosowano do klasyfikacji obrazu odzieży. W porównaniu z pozostałymi siedmioma typami algorytmów klasyfikacji, proponowany model klasyfikacji obrazu odzieży ze zoptymalizowanym przez DA OSELM osiągnął dokładność 93,98%. Jego wydajność przewyższyła inne algorytmy. Na podstawie analizy stabilności wykresu stwierdzono, że nie było wartości odstających wykazywanych przez model DA-OSELM, podczas gdy niektóre inne modele miały wartości odstające lub miały niższą stabilność w porównaniu z proponowanym modelem, potwierdzono w ten sposób skuteczność proponowanego rozwiązania.
    Źródło:
    Fibres & Textiles in Eastern Europe; 2021, 3 (147); 91-96
    1230-3666
    2300-7354
    Pojawia się w:
    Fibres & Textiles in Eastern Europe
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Online Training and Contests for Informatics Contestants of Secondary School Age
    Autorzy:
    NÉMETH,, Ágnes Erdősné
    ZSAKÓ, László
    Powiązania:
    https://bibliotekanauki.pl/articles/457559.pdf
    Data publikacji:
    2015
    Wydawca:
    Uniwersytet Rzeszowski
    Tematy:
    algorithm
    online contest
    online training
    classification
    IOI
    Opis:
    If you prepare students for programming contests carefully selected and widely available online training and contests offer help and diversity. If you teach about testing programs you have to know which sites offer downloadable tests or feedback with detailed test cases. If you want to make series of tasks for practicing you have to know which sites offer you categorized tasks of the appropriate level. In order to be able to choose from the available materials we need to categorize them. The previously defined and used criteria need some supplement criteria for better and sophisticated use of categorization from the teacher’s point of view. Online resources can be classified in general: what programming languages can be used, how often the contests are organized, in which languages they can be accessed, what types of problems a website deals with and at what level, what prior knowledge is required. We can group sites according to whether they help teachers to set tasks for their students, or get ideas for solutions or see the results of their students. Online contests can also be categorized regarding whether students can see each other's solutions. The aim of this paper is to supplement the categorization and describe some major portals according to the previously defined and supplemented criteria.
    Źródło:
    Edukacja-Technika-Informatyka; 2015, 6, 1; 273-280
    2080-9069
    Pojawia się w:
    Edukacja-Technika-Informatyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Elo Rating Algorithm for the Purpose of Measuring Task Difficulty in Online Learning Environments
    Autorzy:
    Pankiewicz, Maciej
    Bator, Maricn
    Powiązania:
    https://bibliotekanauki.pl/articles/425608.pdf
    Data publikacji:
    2019
    Wydawca:
    Szkoła Główna Handlowa w Warszawie
    Tematy:
    Elo
    rating algorithm
    task difficulty
    online learning environment
    learner feedback
    proportion correct
    Opis:
    The Elo rating algorithm, developed for the purpose of measuring player strength in chess tournaments, has also found application in the context of educational research and has been used for the purpose of measuring both learner ability and task difficulty. The quality of the estimations performed by the Elo rating algorithm has already been subject to research, and has been shown to deliver accurate estimations in both low and high-stake testing situations. However, little is known about the performance of the Elo algorithm in the context of learning environments where multiple attempts are allowed, feedback is provided, and the learning process spans several weeks or even months. This study develops the topic of Elo algorithm use in an educational context and examines its performance on real data from an online learning environment where multiple attempts were allowed, and feedback was provided after each attempt. Its performance in terms of stability of the estimation results in two analyzed periods for two groups of learners with different initial levels of knowledge are compared with alternative difficulty estimation methods: proportion correct and learner feedback. According to the results, the Elo rating algorithm outperforms both proportion correct and learning feedback. It delivers stable difficulty estimations, with correlations in the range 0.87–0.92 for the group of beginners and 0.72–0.84 for the group of experienced learners.
    Źródło:
    e-mentor. Czasopismo naukowe Szkoły Głównej Handlowej w Warszawie; 2019, 5 (82); 43-51
    1731-6758
    1731-7428
    Pojawia się w:
    e-mentor. Czasopismo naukowe Szkoły Głównej Handlowej w Warszawie
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Maintaining the feasibility of hard real-time systems with a reduced number of priority levels
    Autorzy:
    Qureshi, M. B.
    Alrashed, S.
    Min-Allah, N.
    Kołodziej, J.
    Arabas, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/330305.pdf
    Data publikacji:
    2015
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    real time system
    feasibility analysis
    fixed priority scheduling
    rate monotonic algorithm
    online scheduling
    system czasu rzeczywistego
    analiza wykonalności
    algorytm szeregowania
    Opis:
    When there is a mismatch between the cardinality of a periodic task set and the priority levels supported by the underlying hardware systems, multiple tasks are grouped into one class so as to maintain a specific level of confidence in their accuracy. However, such a transformation is achieved at the expense of the loss of schedulability of the original task set. We further investigate the aforementioned problem and report the following contributions: (i) a novel technique for mapping unlimited priority tasks into a reduced number of classes that do not violate the schedulability of the original task set and (ii) an efficient feasibility test that eliminates insufficient points during the feasibility analysis. The theoretical correctness of both contributions is checked through formal verifications. Moreover, the experimental results reveal the superiority of our work over the existing feasibility tests by reducing the number of scheduling points that are needed otherwise.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2015, 25, 4; 709-722
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Large-scale hyperspectral image compression via sparse representations based on online learning
    Autorzy:
    Ülkü, İ.
    Kizgut, E.
    Powiązania:
    https://bibliotekanauki.pl/articles/331241.pdf
    Data publikacji:
    2018
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    hyperspectral imaging
    compression algorithm
    dictionary learning
    sparse coding
    obrazowanie wielospektralne
    algorytm kompresji
    nauczanie online
    kodowanie rzadkie
    Opis:
    In this study, proximity based optimization algorithms are used for lossy compression of hyperspectral images that are inherently large scale. This is the first time that such proximity based optimization algorithms are implemented with an online dictionary learning method. Compression performances are compared with the one obtained by various sparse representation algorithms. As a result, proximity based optimization algorithms are listed among the three best ones in terms of compression performance values for all hyperspectral images. Additionally, the applicability of anomaly detection is tested on the reconstructed images.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2018, 28, 1; 197-207
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Online learning algorithm for zero-sum games with integral reinforcement learning
    Autorzy:
    Vamvoudakis, K. G.
    Vrabie, D.
    Lewis, F. L.
    Powiązania:
    https://bibliotekanauki.pl/articles/91780.pdf
    Data publikacji:
    2011
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    learning
    online algorithm
    zero-sum game
    game
    infinite horizon
    Hamilton-Jacobi-Isaacs equation
    approximation network
    optimal value function
    adaptive control tuning algorithm
    Nash solution
    Opis:
    In this paper we introduce an online algorithm that uses integral reinforcement knowledge for learning the continuous-time zero sum game solution for nonlinear systems with infinite horizon costs and partial knowledge of the system dynamics. This algorithm is a data based approach to the solution of the Hamilton-Jacobi-Isaacs equation and it does not require explicit knowledge on the system’s drift dynamics. A novel adaptive control algorithm is given that is based on policy iteration and implemented using an actor/ disturbance/critic structure having three adaptive approximator structures. All three approximation networks are adapted simultaneously. A persistence of excitation condition is required to guarantee convergence of the critic to the actual optimal value function. Novel adaptive control tuning algorithms are given for critic, disturbance and actor networks. The convergence to the Nash solution of the game is proven, and stability of the system is also guaranteed. Simulation examples support the theoretical result.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2011, 1, 4; 315-332
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Applying artificial intelligence algorithms in MOBA games
    Autorzy:
    Wiśniewski, M.
    Niewiadomski, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/92952.pdf
    Data publikacji:
    2016
    Wydawca:
    Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
    Tematy:
    multiplayer online battle arena
    MOBA
    artificial intelligence
    AI
    genetic algorithm
    GA
    computer game
    computer game agents
    bots
    Opis:
    Multiplayer Online Battle Arena games focus mainly on struggles between two teams of players. An increasing level of cyberbullying [1] discourages new players from the game and they often chose a different option, that is, a match against opponents controlled by the computer. The behavior of artificial foes can be dynamically fitted to user’s needs, in particular with regard to the difficulty of the game. In this paper we explore different approaches to provide an intelligent behavior of bots basing on more human-like combat predictions rather than instant, scripted behaviors.
    Źródło:
    Studia Informatica : systems and information technology; 2016, 1-2(20); 53-64
    1731-2264
    Pojawia się w:
    Studia Informatica : systems and information technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Online parameter identification of SPMSM based on improved artificial bee colony algorithm
    Autorzy:
    Wu, Chunli
    Jiang, Shuai
    Bian, Chunyuan
    Powiązania:
    https://bibliotekanauki.pl/articles/1955171.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    artificial bee colony algorithm
    Euclidean distance
    online identification
    parameter identification
    urface-mounted permanent magnet synchronous motor
    algorytm sztucznej kolonii pszczół
    odległość euklidesowa
    identyfikacja online
    identyfikacja parametrów
    silnik synchroniczny z magnesami trwałymi montowany na powierzchni czołowej
    Opis:
    The artificial bee colony (ABC) intelligence algorithm is widely applied to solve multi-variable function optimization problems. In order to accurately identify the parameters of the surface-mounted permanent magnet synchronous motor (SPMSM), this paper proposes an improved ABC optimization method based on vector control to solve the multi-parameter identification problem of the PMSM. Because of the shortcomings of the existing parameter identification algorithms, such as high computational complexity and data saturation, the ABC algorithm is applied for the multi-parameter identification of the PMSM for the first time. In order to further improve the search speed of the ABC algorithm and avoid falling into the local optimum, Euclidean distance is introduced into the ABC algorithm to search more efficiently in the feasible region. Applying the improved algorithm to multi-parameter identification of the PMSM, this method only needs to sample the stator current and voltage signals of the motor. Combined with the fitness function, the online identification of the PMSM can be achieved. The simulation and experimental results show that the ABC algorithm can quickly identify the motor stator resistance, inductance and flux linkage. In addition, the ABC algorithm improved by Euclidean distance has faster convergence speed and smaller steady-state error for the identification results of stator resistance, inductance and flux linkage.
    Źródło:
    Archives of Electrical Engineering; 2021, 70, 4; 777-790
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-11 z 11

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