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Artificial Intelligence Review

, Volume 52, Issue 4, pp 2457–2473 | Cite as

Modified immune network algorithm based on the Random Forest approach for the complex objects control

  • G. A. Samigulina
  • Z. I. SamigulinaEmail author
Article

Abstract

Nowadays application of the methods of artificial intelligence to create automated complex objects control systems in different application areas is topical. The article presents the developed modified algorithm based on artificial immune system, in which the Random Forest algorithm is used for data pre-processing and extraction of informative signs describing the behavior of a complex object of control. There are presented the results of aircraft flight simulation based on Ailerons database with the help of WEKA software and RStudio environment. There was made the comparative analysis of the modified immune network algorithm with different data pre-processing (based on the Random Forest and factor analysis).

Keywords

Complex objects control Artificial intelligence Artificial immune systems Random Forest Factor analysis Feature extraction 

Notes

Acknowledgements

The work is carried out under the Grant of SC MES of the Republic of Kazakhstan GR0215RK01472 (2015–2017) on the theme “Development of information technology, algorithms, software and hardware for intelligent systems of complex objects control in the condition of parameter uncertainties”.

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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Intellectual Control Systems and ForecastingInstitute of Information and Computing Technologies, IICTAlmatyKazakhstan
  2. 2.Faculty of the Information TechnologyKazakh-British Technical University, KBTUAlmatyKazakhstan

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