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Wyszukujesz frazę "evolutionary algorithm" wg kryterium: Temat

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    Wyświetlanie 1-4 z 4
    Tytuł:
    Evolutionary algorithm for selecting dynamic signatures partitioning approach
    Autorzy:
    Zalasiński, Marcin
    Laskowski, Łukasz
    Niksa-Rynkiewicz, Tacjana
    Cpałka, Krzysztof
    Byrski, Aleksander
    Przybyszewski, Krzysztof
    Trippner, Paweł
    Dong, Shi
    Powiązania:
    https://bibliotekanauki.pl/articles/2147146.pdf
    Data publikacji:
    2022
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    identity verification
    dynamic signature
    hybrid partitions
    partitions’ selection
    evolutionary algorithm
    Opis:
    In the verification of identity, the aim is to increase effectiveness and reduce involvement of verified users. A good compromise between these issues is ensured by dynamic signature verification. The dynamic signature is represented by signals describing the position of the stylus in time. They can be used to determine the velocity or acceleration signal. Values of these signals can be analyzed, interpreted, selected, and compared. In this paper, we propose an approach that: (a) uses an evolutionary algorithm to create signature partitions in the time and velocity domains; (b) selects the most characteristic partitions in terms of matching with reference signatures; and (c) works individually for each user, eliminating the need of using skilled forgeries. The proposed approach was tested using Biosecure DS2 database which is a part of the DeepSignDB, a database with genuine dynamic signatures. Our simulations confirmed the correctness of the adopted assumptions.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 4; 267--279
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Evolutionary algorithm with a configurable search mechanism
    Autorzy:
    Łapa, Krystian
    Cpałka, Krzysztof
    Laskowski, Łukasz
    Cader, Andrzej
    Zeng, Zhigang
    Powiązania:
    https://bibliotekanauki.pl/articles/1837536.pdf
    Data publikacji:
    2020
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    evolutionary algorithm
    population-based algorithm
    optimization
    operator pool
    operator selection
    individual selection
    Opis:
    In this paper, we propose a new population-based evolutionary algorithm that automatically configures the used search mechanism during its operation, which consists in choosing for each individual of the population a single evolutionary operator from the pool. The pool of operators comes from various evolutionary algorithms. With this idea, a flexible balance between exploration and exploitation of the problem domain can be achieved. The approach proposed in this paper might offer an inspirational alternative in creating evolutionary algorithms and their modifications. Moreover, different strategies for mutating those parts of individuals that encode the used search operators are also taken into account. The effectiveness of the proposed algorithm has been tested using typical benchmarks used to test evolutionary algorithms.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 3; 151-171
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Optimization of traveling salesman problem using affinity propagation clustering and genetic algorithm
    Autorzy:
    El-Samak, A. F.
    Ashour, W.
    Powiązania:
    https://bibliotekanauki.pl/articles/91810.pdf
    Data publikacji:
    2015
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    combinatorial optimization problem
    travel salesman problem
    genetic algorithm
    evolutionary computation algorithm
    affinity propagation clustering technique
    AP
    problem optymalizacji kombinatorycznej
    algorytm genetyczny
    obliczenia ewolucyjne
    Opis:
    Combinatorial optimization problems, such as travel salesman problem, are usually NPhard and the solution space of this problem is very large. Therefore the set of feasible solutions cannot be evaluated one by one. The simple genetic algorithm is one of the most used evolutionary computation algorithms, that give a good solution for TSP, however, it takes much computational time. In this paper, Affinity Propagation Clustering Technique (AP) is used to optimize the performance of the Genetic Algorithm (GA) for solving TSP. The core idea, which is clustering cities into smaller clusters and solving each cluster using GA separately, thus the access to the optimal solution will be in less computational time. Numerical experiments show that the proposed algorithm can give a good results for TSP problem more than the simple GA.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2015, 5, 4; 239-245
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Advanced supervision of oil wells based on soft computing techniques
    Autorzy:
    Camargo, E.
    Aguilar, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/91828.pdf
    Data publikacji:
    2014
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    intelligent model of supervision
    evolutionary computation
    fuzzy system
    oil industry
    operational diagnosis
    petroleum wells
    gas lift method
    multilayer fuzzy system
    genetic algorithm
    Opis:
    In this work is presented a hybrid intelligent model of supervision based on Evolutionary Computation and Fuzzy Systems to improve the performance of the Oil Industry, which is used for Operational Diagnosis in petroleum wells based on the gas lift (GL) method. The model is composed by two parts: a Multilayer Fuzzy System to identify the operational scenarios in an oil well and a genetic algorithm to maximize the production of oil and minimize the flow of gas injection, based on the restrictions of the process and the operational cost of production. Additionally, the first layers of the Multilayer Fuzzy System have specific tasks: the detection of operational failures, and the identification of the rate of gas that the well requires for production. In this way, our hybrid intelligent model implements supervision and control tasks.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2014, 4, 3; 215-225
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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