Autor: Skaruz, J. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Combining SMT and Simulated Annealing into a Hybrid Planning Method
Autorzy:: Skaruz, J.
Niewiadomski, A.
Penczek, W.
Powiązania:: https://bibliotekanauki.pl/articles/92934.pdf
Data publikacji:: 2015
Wydawca:: Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:: concrete planning
genetic algorithm
satisfiability modulo theories
simulated annealing
web service composition
planics
Opis:: We present a new approach to the concrete planning (CP) - a stage of theWeb service composition in the PlanICS framework. A new hybrid algorithm (HSA) based on a combination of Simulated Annealing (SA) with Satisfiability Modulo Theories (SMT) has been designed and implemented. The main idea of our hybrid solution is to use an SMT-based procedure in order to generate an initial individual and then improve it during subsequent iterations of SA. The experimental results show that HSA is superior to the other methods we have applied to the CP problem, including Genetic Algorithm, an SMT-based approach, and our previously developed hybrids.
Źródło:: Studia Informatica : systems and information technology; 2015, 1-2(19); 43-48
1731-2264
Pojawia się w:: Studia Informatica : systems and information technology
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Image reconstruction with the use of evolutionary algorithms and cellular automata
Autorzy:: Seredyński, F.
Skaruz, J.
Piraszewski, A.
Powiązania:: https://bibliotekanauki.pl/articles/106216.pdf
Data publikacji:: 2012
Wydawca:: Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Tematy:: image reconstruction
evolution algorithms
cellular automata
genetic algorithm
Opis:: In the paper we present a new approach to the image reconstruction problem based on evolution algorithms and cellular automata. Two-dimensional, nine state cellular automata with the Moore neighbourhood perform reconstruction of an image presenting a human face. Large space of automata rules is searched through efficiently by the genetic algorithm (GA), which finds a good quality rule. The experimental results show that the obtained rule allows to reconstruct an image with even 70% damaged pixels. Moreover, we show that the rule found in the genetic evolution process can be applied to the reconstruction of images of the same class but not presented during the evolutionary one.
Źródło:: Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica; 2012, 12, 4; 39-49
1732-1360
2083-3628
Pojawia się w:: Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica
Dostawca treści:: Biblioteka Nauki

Artykuł

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