Problem-oriented knowledge processing on the basis of hybrid approach

DOI

10.2991/itsmssm-16.2016.15How to use a DOI?

Keywords

Genetic algorithm, Evolutionary algorithm, Hybrid approach, Adaptation, Neighborhood, Population, Self-organization, Problem-oriented knowledge

Abstract

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.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of the 2016 Conference on 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  - 10.2991/itsmssm-16.2016.15
ID  - Kuliev2016/05
ER  -