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    Wyświetlanie 1-2 z 2
    Tytuł:
    Causal reversibility in individual token interpretation of Petri Nets
    Autorzy:
    Benamira, Adel
    Powiązania:
    https://bibliotekanauki.pl/articles/1839245.pdf
    Data publikacji:
    2020
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    reversibility
    concurrent systems
    Petri Nets
    causality
    Opis:
    Causal reversibility in concurrent systems means that events that the origin of other events can only be undone after undoing its consequences. In opposition to backtracking, events that are independent of each other can be reversed in an arbitrary order; in other words, we have flexible reversibility with respect to a causality relationship. An implementation of individual token interpretation of Petri Nets (IPNs) has been proposed by Rob Van Glabbeek et al.; the present paper investigates a study of causal reversibility within IPNs. Given N as an IPN, by adding an intuitive firing rule to undo transitions according to the causality relationship, the coherence of N is assured; i.e., the set of all reachable states of N in the reversible version and that of the original one are identical. Furthermore, reversibility in N is flexible, and their initial state can be accessible in reverse from any state. In this paper, an approach for controlling causal-reversibility within IPNs is proposed.
    Źródło:
    Computer Science; 2020, 21 (4); 489-511
    1508-2806
    2300-7036
    Pojawia się w:
    Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Modelling Microcystis Cell Density in a Mediterranean Shallow Lake of Northeast Algeria (Oubeira Lake), Using Evolutionary and Classic Programming
    Autorzy:
    Arif, Salah
    Djellal, Adel
    Djebbari, Nawel
    Belhaoues, Saber
    Touati, Hassen
    Guellati, Fatma Zohra
    Bensouilah, Mourad
    Powiązania:
    https://bibliotekanauki.pl/articles/2174666.pdf
    Data publikacji:
    2023
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    microcystis cell density
    Multiple Linear Regression
    Support Vector Machine
    Particle Swarm Optimization
    Genetic Algorithm
    Bird Swarm Algorithm
    Opis:
    Caused by excess levels of nutrients and increased temperatures, freshwater cyanobacterial blooms have become a serious global issue. However, with the development of artificial intelligence and extreme learning machine methods, the forecasting of cyanobacteria blooms has become more feasible. We explored the use of multiple techniques, including both statistical [Multiple Regression Model (MLR) and Support Vector Machine (SVM)] and evolutionary [Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Bird Swarm Algorithm (BSA)], to approximate models for the prediction of Microcystis density. The data set was collected from Oubeira Lake, a natural shallow Mediterranean lake in the northeast of Algeria. From the correlation analysis of ten water variables monitored, six potential factors including temperature, ammonium, nitrate, and ortho-phosphate were selected. The performance indices showed; MLR and PSO provided the best results. PSO gave the best fitness but all techniques performed well. BSA had better fitness but was very slow across generations. PSO was faster than the other techniques and at generation 20 it passed BSA. GA passed BSA a little further, at generation 50. The major contributions of our work not only focus on the modelling process itself, but also take into consideration the main factors affecting Microcystis blooms, by incorporating them in all applied models.
    Źródło:
    Geomatics and Environmental Engineering; 2023, 17, 2; 31--68
    1898-1135
    Pojawia się w:
    Geomatics and Environmental Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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