Describing the swarm algorithms, inspired by abiocen and bacterias, in the bionics ontology

О.С. Смирнова, А.В. Богорадникова, М.Ю. Блинов

Abstract


The paper provides a detailed review of swarm algorithms, inspired by abiocen and bacterias, to be used in the population of bionics ontology.

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References


Sigov A.S., Nechaev V.V., Koshkarev M.I. Arhitektura predmetno-orientirovannoj bazy znanij intellektual'noj sistemy. International Journal of Open Information Technologies ISSN: 2307-8162 vol. 2, no.12, 2014.

Sigov A.S., Nechaev V.V., Baranyuk V.V., Koshkarev M.I., Smirnova O.S., Melikhov A.A., Bogoradnikova A.V. Architecture of domain-specific data warehouse for bionic information resources. Ecology, environment and conservation, #4, 2015.

Baranjuk V.V., Smirnova O.S. Roevoj intellekt kak odna iz chastej ontologicheskoj modeli bionicheskih tehnologij. International Journal of Open Information Technologies. Vol.3, no. 12, 2015.

Baranjuk V.V., Smirnova O.S. Detalizacija ontologicheskoj modeli po roevym algoritmam, osnovannym na povedenii nasekomyh i zhivotnyh. International Journal of Open Information Technologies. Vol. 3, no. 12, 2015.

Gravitacionnyj poisk. Jel. resurs: http://www.pvsm.ru/algoritmy/44008/print/

Shah-Hosseini H. The intelligent water drops algorithm: a nature-inspired swarm-based optimization algorithm. // Int. J. Bio-Inspired Comput. 1, 1/2 (January 2009). Geneva: Inderscience Publishers. – 2009. – s.71-79.

Zadacha kommivojazhjora. Jel. Resurs: http://dic.academic.ru/dic.nsf/ruwiki/25185

Karpenko A.P. Populjacionnye algoritmy global'noj poiskovoj optimizacii. Obzor novyh i maloizvestnyh algoritmov. Zhurnal «Informacionnye tehnologii», Prilozhenie, #7/2012 g. Izd.: «Novye tehnologii», 32 s.

Das S., Biswas A., Dasgupta S., Abraham A. Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications// Foundations of Computational Intelligence. Publisher: Springer. 2009. V. 203. P. 23–55.

Chen H., Zhu Yu., Hu K. Cooperative Bacterial Foraging Optimization // Discrete Dynamics in Nature and Society. 2009. V. 2009. P. 1–17.

Eiben A. E., Michalewicz Z., Schoenauer M, Smith J. E. Parameter Control in Evolutionary Algorithms // Parameter Setting in Evolutionary Algorithms. Springer Verlag. 2007. P. 19–46.

Kim D. H., Abraham A., Cho J. H. A hybrid genetic algorithm and bacterial foraging approach for global optimization // Information Sciences. 2007. V. 177. P. 3918–3937.

El-Abd, Kamel M. A taxonomy of cooperative search algorithms // Hybrid Metaheuristics: Second International Workshop. Springer. 2005. V. 3636. P. 32–41.

Raidl G. R. A Unified View on Hybrid Metaheuristics // Lecture Notes in Computer Science. Springer-Verlag. 2006. V. 4030. P. 1–12.

Datta T., Misra I. S., Mangaraj B.B., Imtiaj S. Improved adaptive bacteria foraging algorithm in optimization of antenna array for faster convergence // Progress In Electromagnetics Research. 2008. V. 1. P. 143–157.

Kurejchik V. M. Geneticheskie algoritmy i ih primenenie. Taganrog: Izd-vo Taganrogskogo RTU. 2002. S. 244.

Korani W. M, Dorrah H. T, Emara H. M. Bacterial Foraging Oriented by Particle Swarm Optimization Strategy for PID Tuning// Computational Intelligence in Robotics and Automation (CIRA). IEEE International Symposium on 15–18 Dec. 2009. P. 445–450.

Baranjuk V.V., Smirnova O.S., Bogoradnikova A.V. Intellektual'naja sistema informacionnoj podderzhki razvitija perspektivnyh bionicheskih tehnologij: osnovnye napravlenija rabot po sozdaniju. International Journal of Open Information Technologies ISSN: 2307-8162 vol. 2, no. 12, 2014.


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