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    Wyświetlanie 1-4 z 4
    Tytuł:
    Research on hybrid modified pathfinder algorithm for optimal reactive power dispatch
    Autorzy:
    Suresh, V.
    Senthil Kumar, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/2086822.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    optimal reactive power dispatch
    ORPD
    real-power losses
    pathfinder algorithm
    PFA
    modified pathfinder algorithm
    mPFA
    hybrid pathfinder algorithm
    HPFA
    optymalna dyspozycja mocy biernej
    strata mocy rzeczywistej
    algorytm wyszukiwania najkrótszej drogi
    algorytm wyszukiwania najkrótszej drogi zmodyfikowany
    algorytm wyszukiwania najkrótszej drogi hybrydowy
    Opis:
    Hybridization of meta-heuristic algorithms plays a major role in the optimization problem. In this paper, a new hybrid meta-heuristic algorithm called hybrid pathfinder algorithm (HPFA) is proposed to solve the optimal reactive power dispatch (ORPD) problem. The superiority of the Differential Evolution (DE) algorithm is the fast convergence speed, a mutation operator in the DE algorithm incorporates into the pathfinder algorithm (PFA). The main objective of this research is to minimize the real power losses and subject to equality and inequality constraints. The HPFA is used to find optimal control variables such as generator voltage magnitude, transformer tap settings and capacitor banks. The proposed HPFA is implemented through several simulation cases on the IEEE 118-bus system and IEEE 300-bus power system. Results show the superiority of the proposed algorithm with good quality of optimal solutions over existing optimization techniques, and hence confirm its potential to solve the ORPD problem.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 4; e137733, 1--8
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    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:
    Optimization of the process of restoring the continuity of the WDS based on the matrix and genetic algorithm approach
    Autorzy:
    Antonowicz, Ariel
    Urbaniak, Andrzej
    Powiązania:
    https://bibliotekanauki.pl/articles/2173692.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    WNTR
    Water Network Tool for Resilience
    aggregation of failures
    water distribution system
    EPANET Solver
    Graph Searching Algorithms
    genetic algorithm
    optimization
    post-disaster events
    agregacja awarii
    system dystrybucji wody
    EPANET
    algorytm wyszukiwania grafów
    algorytm genetyczny
    optymalizacja
    wydarzenia po katastrofie
    Opis:
    The article discusses an example of the use of graph search algorithms with trace of water analysis and aggregation of failures in the occurrence of a large number of failures in the Water Supply System (WSS). In the event of a catastrophic situation, based on the Water Distribution System (WDS) network model, information about detected failures, the condition and location of valves, the number of repair teams, criticality analysis, the coefficient of prioritization of individual network elements, and selected objective function, the algorithm proposes the order of repairing the failures should be analyzed. The approach proposed by the authors of the article assumes the selection of the following objective function: minimizing the time of lack of access to drinking water (with or without prioritization) and minimizing failure repair time (with or without failure aggregation). The algorithm was tested on three different water networks (small, medium, and large numbers of nodes) and three different scenarios (different numbers of failures and valves in the water network) for each selected water network. The results were compared to a valve designation approach for closure using an adjacency matrix and a Strategic Valve Management Model (SVMM).
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 4; art. no. e141594
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Lung cancer detection using an integration of fuzzy K-Means clustering and deep learning techniques for CT lung images
    Autorzy:
    Prasad, J. Maruthi Nagendra
    Chakravarty, S.
    Krishna, M. Vamsi
    Powiązania:
    https://bibliotekanauki.pl/articles/2173683.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    fuzzy K-means
    artificial neural networks
    SVM
    support vector machine
    crow search optimization algorithm
    algorytm rozmytych k-średnich
    sztuczne sieci neuronowe
    maszyna wektorów wspierających
    algorytm optymalizacji wyszukiwania kruków
    Opis:
    Computer aided detection systems are used for the provision of second opinion during lung cancer diagnosis. For early-stage detection and treatment false positive reduction stage also plays a vital role. The main motive of this research is to propose a method for lung cancer segmentation. In recent years, lung cancer detection and segmentation of tumors is considered one of the most important steps in the surgical planning and medication preparations. It is very difficult for the researchers to detect the tumor area from the CT (computed tomography) images. The proposed system segments lungs and classify the images into normal and abnormal and consists of two phases, The first phase will be made up of various stages like pre-processing, feature extraction, feature selection, classification and finally, segmentation of the tumor. Input CT image is sent through the pre-processing phase where noise removal will be taken care of and then texture features are extracted from the pre-processed image, and in the next stage features will be selected by making use of crow search optimization algorithm, later artificial neural network is used for the classification of the normal lung images from abnormal images. Finally, abnormal images will be processed through the fuzzy K-means algorithm for segmenting the tumors separately. In the second phase, SVM classifier is used for the reduction of false positives. The proposed system delivers accuracy of 96%, 100% specificity and sensitivity of 99% and it reduces false positives. Experimental results shows that the system outperforms many other systems in the literature in terms of sensitivity, specificity, and accuracy. There is a great tradeoff between effectiveness and efficiency and the proposed system also saves computation time. The work shows that the proposed system which is formed by the integration of fuzzy K-means clustering and deep learning technique is simple yet powerful and was effective in reducing false positives and segments tumors and perform classification and delivers better performance when compared to other strategies in the literature, and this system is giving accurate decision when compared to human doctor’s decision.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 3; art. no. e139006
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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