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

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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).

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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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Authors and Affiliations

  1. Intellectual Control Systems and Forecasting, Institute of Information and Computing Technologies, IICT, Almaty, Kazakhstan

    G. A. Samigulina

  2. Faculty of the Information Technology, Kazakh-British Technical University, KBTU, Almaty, Kazakhstan

    Z. I. Samigulina

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  1. G. A. Samigulina
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  2. Z. I. Samigulina
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Correspondence to Z. I. Samigulina.

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Samigulina, G.A., Samigulina, Z.I. Modified immune network algorithm based on the Random Forest approach for the complex objects control. Artif Intell Rev 52, 2457–2473 (2019). https://doi.org/10.1007/s10462-018-9621-7

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  • DOI: https://doi.org/10.1007/s10462-018-9621-7

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