Problem-oriented knowledge processing on the basis of hybrid approach
Elmar Kuliev, Yury Kravchenko, Nina Kulieva, Vladimir Kureichik
Available Online May 2016.
- https://doi.org/10.2991/itsmssm-16.2016.15How to use a DOI?
- Genetic algorithm, Evolutionary algorithm, Hybrid approach, Adaptation, Neighborhood, Population, Self-organization, Problem-oriented knowledge
- The paper discusses a hybridization of adaptation mechanisms with self-organization in order to process problem-oriented knowledge. The core of the proposed method consists in sequential execution of bionic and genetic algorithms. To demonstrate the hybrid algorithm we gave an example of a solution search. In the paper it is presented a formulation of the problem-oriented knowledge processing task during the optimal solution search.. To solve this problem we developed a modified architecture of the hybrid search. The suggested architecture involves principal components of a bioinspired search. To improve the algorithm performance we provide an opportunity to add new algorithms with an evolutionary adaptation module and environment module. . Conducted experiments confirmed that time complexity of the developed approach is polynomial.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Elmar Kuliev AU - Yury Kravchenko AU - Nina Kulieva AU - Vladimir Kureichik PY - 2016/05 DA - 2016/05 TI - Problem-oriented knowledge processing on the basis of hybrid approach BT - Information Technologies in Science, Management, Social Sphere and Medicine PB - Atlantis Press SP - 70 EP - 73 SN - 2352-538X UR - https://doi.org/10.2991/itsmssm-16.2016.15 DO - https://doi.org/10.2991/itsmssm-16.2016.15 ID - Kuliev2016/05 ER -