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Wyszukujesz frazę "Byrski, Aleksander" wg kryterium: Autor


Wyświetlanie 1-7 z 7
Tytuł:
A new approach to detecting and preventing populations stagnation through dynamic changes in multi-population-based algorithms
Autorzy:
Łapa, Krystian
Rutkowska, Danuta
Byrski, Aleksander
Napoli, Christian
Powiązania:
https://bibliotekanauki.pl/articles/23944836.pdf
Data publikacji:
2023
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
multi-population-based algorithms
migration topologies
population stagnation
Opis:
In this paper, a new mechanism for detecting population stagnation based on the analysis of the local improvement of the evaluation function and the infinite impulse response filter is proposed. The purpose of this mechanism is to improve the population stagnation detection capability for various optimization scenarios, and thus to improve multi-population-based algorithms (MPBAs) performance. In addition, various other approaches have been proposed to eliminate stagnation, including approaches aimed at both improving performance and reducing the complexity of the algorithms. The developed methods were tested, among the others, for various migration topologies and various MPBAs, including the MNIA algorithm, which allows the use of many different base algorithms and thus eliminates the need to select the population-based algorithm for a given simulation problem. The simulations were performed for typical benchmark functions and control problems. The obtained results confirm the validity of the developed method.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2023, 13, 4; 289--306
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fine tuning of agent-based evolutionary computing
Autorzy:
Mizera, Michal
Nowotarski, Pawel
Byrski, Aleksander
Kisiel-Dorohinicki, Marek
Powiązania:
https://bibliotekanauki.pl/articles/91820.pdf
Data publikacji:
2019
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
multi-agent systems
metaheuristics
evolutionary computing
Opis:
Evolutionary Multi-agent System introduced by late Krzysztof Cetnarowicz and developed further at the AGH University of Science and Technology became a reliable optimization system, both proven experimentally and theoretically. This paper follows a work of Byrski further testing and analyzing the efficacy of this metaheuristic based on popular, high-dimensional benchmark functions. The contents of this paper will be useful for anybody willing to apply this computing algorithm to continuous and not only optimization.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2019, 9, 2; 81-97
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A novel approach to type-reduction and design of interval type-2 fuzzy logic systems
Autorzy:
Starczewski, Janusz T.
Przybyszewski, Krzysztof
Byrski, Aleksander
Szmidt, Eulalia
Napoli, Christian
Powiązania:
https://bibliotekanauki.pl/articles/2147137.pdf
Data publikacji:
2022
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
smooth type-reduction
interval type-2 fuzzy logic systems
Opis:
Fuzzy logic systems, unlike black-box models, are known as transparent artificial intelligence systems that have explainable rules of reasoning. Type 2 fuzzy systems extend the field of application to tasks that require the introduction of uncertainty in the rules, e.g. for handling corrupted data. Most practical implementations use interval type-2 sets and process interval membership grades. The key role in the design of type-2 interval fuzzy logic systems is played by the type-2 inference defuzzification method. In type-2 systems this generally takes place in two steps: type-reduction first, then standard defuzzification. The only precise type-reduction method is the iterative method known as Karnik-Mendel (KM) algorithm with its enhancement modifications. The known non-iterative methods deliver only an approximation of the boundaries of a type-reduced set and, in special cases, they diminish the profits that result from the use of type-2 fuzzy logic systems. In this paper, we propose a novel type-reduction method based on a smooth approximation of maximum/minimum, and we call this method a smooth type-reduction. Replacing the iterative KM algorithm by the smooth type-reduction, we obtain a structure of an adaptive interval type-2 fuzzy logic which is non-iterative and as close to an approximation of the KM algorithm as we like.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 3; 197--206
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Microscopic simulation of pedestrian traffic in urban environment under epidemic conditions
Autorzy:
Paciorek, Mateusz
Poklewski-Koziełł, Damian
Racoń-Leja, Kinga
Byrski, Aleksander
Gyurkovich, Mateusz
Turek, Wojciech
Powiązania:
https://bibliotekanauki.pl/articles/2086861.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
epidemic modeling
pedestrian dynamic simulation
urban environment
modelowanie epidemii
symulacja dynamiki pieszych
środowisko miejskie
Opis:
The ongoing period of the pandemic makes everybody focused on the matters related to fighting this immense problem posed to the societies worldwide. The governments deal with the threat by publishing regulations which should allow to mitigate the pandemic, walking on thin ice as the decision makers do not always know how to properly respond to the threat in order to save people. Computer-based simulations of e.g. parts of the city or rural area should provide significant help, however, there are some requirements to fulfill. The simulation should be verifiable, supported by the urban research and it should be possible to run it in appropriate scale. Thus in this paper we present an interdisciplinary work of urban researchers and computer scientists, proposing a scalable, HPC-grade model of simulation, which was tested in a real scenario and may be further used to extend our knowledge about epidemic spread and the results of its counteracting methods. The paper shows the relevant state of the art, discusses the micro-scale simulation model, sketches out the elements of its implementation and provides tangible results gathered for a part of the city of Krakow, Poland.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 4; e137725, 1--15
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Combined YOLOv5 and HRNet for high accuracy 2D keypoint and human pose estimation
Autorzy:
Nguyen, Hung-Cuong
Nguyen, Thi-Hao
Nowak, Jakub
Byrski, Aleksander
Siwocha, Agnieszka
Le, Van-Hung
Powiązania:
https://bibliotekanauki.pl/articles/2147147.pdf
Data publikacji:
2022
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
YOLOv5
HRNet
2D key points estimation
2D human pose estimation
Opis:
Two-dimensional human pose estimation has been widely applied in real-world applications such as sports analysis, medical fall detection, human-robot interaction, with many positive results obtained utilizing Convolutional Neural Networks (CNNs). Li et al. at CVPR 2020 proposed a study in which they achieved high accuracy in estimating 2D keypoints estimation/2D human pose estimation. However, the study performed estimation only on the cropped human image data. In this research, we propose a method for automatically detecting and estimating human poses in photos using a combination of YOLOv5 + CC (Contextual Constraints) and HRNet. Our approach inherits the speed of the YOLOv5 for detecting humans and the efficiency of the HRNet for estimating 2D keypoints/2D human pose on the images. We also performed human marking on the images by bounding boxes of the Human 3.6M dataset (Protocol #1) for human detection evaluation. Our approach obtained high detection results in the image and the processing time is 55 FPS on the Human 3.6M dataset (Protocol #1). The mean error distance is 5.14 pixels on the full size of the image (1000×1002). In particular, the average results of 2D human pose estimation/2D keypoints estimation are 94.8% of PCK and 99.2% of PDJ@0.4 (head joint). The results are available.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 4; 281--298
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Population diversity in ant-inspired optimization algorithms
Autorzy:
Byrski, Aleksander
Węgrzyński, Krzysztof
Radwański, Wojciech
Starzec, Grażyna
Starzec, Mateusz
Bargiel, Monika
Urbańczyk, Aleksandra
Kisiel-Dorohinicki, Marek
Powiązania:
https://bibliotekanauki.pl/articles/2097962.pdf
Data publikacji:
2021
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
ant colony optimization
diversity measuring
exploitation and exploration balance
metaheuristics
Opis:
Measuring the diversity in evolutionary algorithms that work in real-value search spaces is often computationally complex, but it is feasible; however, measuring the diversity in combinatorial domains is practically impossible. Nevertheless, in this paper we propose several practical and feasible diversitymeasurement techniques that are dedicated to ant colony optimization algorithms, leveraging the fact that we can focus on a pheromone table even though an analysis of the search space is at least an NP problem where the direct outcomes of the search are expressed and can be analyzed. Besides sketching out the algorithms, we apply them to several benchmark problems and discuss their efficacy.
Źródło:
Computer Science; 2021, 22 (3); 297-320
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
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
    Wyświetlanie 1-7 z 7

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