Modified immune network algorithm based on the Random Forest approach for the complex objects control
作者:G. A. Samigulina, Z. I. Samigulina
摘要
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).
论文关键词:Complex objects control, Artificial intelligence, Artificial immune systems, Random Forest, Factor analysis, Feature extraction
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论文官网地址:https://doi.org/10.1007/s10462-018-9621-7