1. JCPEE
  2. All Volumes and Issues
  3. Volume 4, Number 2, 2014
  4. Method of structure identification for interval difference operator based on the principles of honey bee colony functioning

Method of structure identification for interval difference operator based on the principles of honey bee colony functioning

JCPEE.
2014;
Volume 4, Number 2
: pp. 57-68
Authors:
  1. Nataliya Porplytsya
  2. Mykola Dyvak
  3. Taras Dyvak
1
Ternopil National Economic University
2
West Ukrainian National University
3
Western Ukrainian National University

In the article, the problem of structure identification of the interval difference operator (IDO) as a model of distributed parameters object is considered. A new method of structure identification of the IDO based on the foraging behavior of a honey bee colony has been proposed and verified. In addition, a neural-like computational scheme of the implementation of the method has been developed. The effectiveness of using the proposed method and its computational scheme are shown on the example of building a macromodel for the prediction of humidity distribution on a drywall sheet in the process of its drying.

Structure identification
interval difference operator
artificial bee colony algorithm
interval data.
  1. A.G. Ivakhnenko, Long-term forecasting and management of complex systems. Kyiv, Ukraine: Tekhnіka, 1975. (Russian)
  2. D. Graupe, Identification of systems, 2nd ed. New York, USA: Robert E. Krieger Publishing Company, 1976.
  3.  Sean Luke, “Essentials of Metaheuristics”, http://cs.gmu.edu/~sean/book/metaheuristics/Essentials.pdf, October, 2014.
  4. I. Voytyuk, M. Dyvak, and V. Nemish, “Method and genetic algorithm for structure identification of interval differentice operators in the tasks of environmental monitoring”, Informatyka, kiybernetyka ta obchysliuvalna tekhnika - Collected Works of Donetsk National Technical University, vol. 188, no. 14, pp. 8-17, 2011. (Ukrainian)
  5. I. Voytyuk,  “Method of structure identification for macromodels as interval difference operators”, in Proc. Conference of young scientists-  Mathematical Modelling in Engineering and Technology, pp. 11-16, Russia, Moscow, 2011. (Russian)
  6. N. Porplytsya and M. Dyvak, “Synthesis of structure of interval difference operator using artifitional bee colony algorithm”, Induktyvne modeliuvannia skladnykh system, vol. 5, pp. 256-269, Kyiv, Ukraine, 2013. (Ukrainian)
  7. T. Dyvak, “Parametric identification of interval difference operator on the example of macromodel for distribution of humidity in the drywall sheets in the process of drying”, Information Technologies and Computer Engineering: International Scientific Journal, vol. 3, pp. 79-85, 2012. (Ukrainian)
  8. M. Dyvak and T.  Dyvak, “Features of construction of interval systems of algebraic equations and methods of solving problems in identification of interval linear difference operator”, Induktyvne modeliuvannia skladnykh system, vol. 1, pp. 35-43, Kyiv, Ukraine, 2009. (Ukrainian)
  9. A.G. Ivakhnenko and A.G. Ivakhnenko, The inductive method for self-organizing models of complex systems,  Kyiv, Ukraine: "Naukova dumka", 1982. - 296 с. (Russian)
  10. D. Karaboga, “An idea based on honey bee swarm for numerical optimization”, Technical Report TR06, Computer Engineering Department, Engineering Faculty, Erciyes University, Turkey, 2005.
  11. D. Karaboga and B. Basturk, “A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm”, Journal of Global Optimization, vol. 39, pp. 459-471, 2007.