The Combined Immune Algorithm Based on Clonal Selection. Litvinenko V.I.,Bidjuk P.I., Bardachov J.N., Fefelov A.A.,Sherstjuk V.G. IWIM, Prague, 2007.
Article (in pdf)
Abstract. A dynamic system identification algorithm is developed using the basic mechanisms of clonal selection and an idea of a new evolutionary computing paradigm – gene expression programming. On the basis of the algorithm developed a computer based system is proposed for making decisions relevant to forecasting of a single variable and multivariate time series. The results of computing experiments achieved with the system developed show high quality of short and medium period forecasts.
Keywords. Artificial immune systems, Clonal selection algorithm, Gene expression programming, Hybrid algorithm
References.
- Bidyuk P.I., Backlan I.V., Litvinenko V.I. (2003), “Modelling and forecasting of heteroscedastic processes,” Automatics, automation, automatic complexes and systems, N. 2(12), pp. 11-19.
- D. Dasgupta (editor), “Artificial Immune Systems and Their Applications,” A book published by Springer Verlag Inc., January 1999.
- Ferreira, C., (2001), “Gene Expression Programming: A New Adaptive Algorithm for Solving Problems,” Complex Systems.
- De Castro, L. N. & Von Zuben, F. J. (2000a), “The Clonal Selection Algorithm with Engineering Applications”, submitted to GECCO’00.
- Litvinenko V.I., Fefelov A.A., Goravski S.P. (2003), “Object-oriented realization of clonal selection algorithm,” Radio electronics, computer science, management, Zaporozhie, N. 9, pp. 81-88.
- Gritsik V.V., Litvinenko V.I., Tsmots I. G., Stekh S.M. (2003), “Theoretical and applied problems of use of artificial immune systems,” Information technologies and systems, vol. 6, N1-2, pp. 7-45.
- Ivahnenko A.G., Stepashko V.S. (1984), “Noise stability of modelling,” A scientific idea, Kiev, 295 p.
