Adaptation of mechanisms of artificial immune systems to control environmental parameters

A.V. Skatkov, A.A. Bryukhovetsky, D.V. Moiseev

 Sevastopol State University, RF, Sevastopol, Universitetskaya St., 33

Email: dmitriymoiseev@mail.ru

DOI: 10.33075/2220-5861-2020-2-127-133

UDC 004.89                                                               

Abstract:

   The paper describes the adaptation of mechanisms of artificial immune systems for their use in environmental control systems. To be able to predict the state of the environment, the identification problem arises, which consists in finding the capacity of pollution sources based on available experimental data. As we know, artificial immune systems (AIS) are successfully used for optimization, classification and identification tasks.in addition, AIS are used for information compression, clustering, anomaly search, machine learning, unstructured data processing and information retrieval, computer security and adaptive control.

   When predicting the state of the environment, the identification problem arises, which consists in finding the capacity of pollution sources based on available experimental data. As you know, artificial immune systems are successfully used to solve this kind of problems. the paper studies mathematical models of enhancing the immune response, artificial immune systems, which are systems of ordinary differential equations. For the first time, it is proposed to accumulate an anti-virus database ahead of time in order to increase the effectiveness of anti-virus measures. The analysis of the obtained results allows us to conclude that the adaptation of mechanisms of artificial immune systems by modifying classical mathematical models in accordance with the specifics of the AIS significantly increases their effectiveness in predicting the state of the environment. The development of artificial intelligence and unmanned control and monitoring tools built using it allows using the mechanisms of artificial immune systems to control environmental parameters in offline mode.

Keywords: artificial intelligence, unmanned control systems, artificial immune systems.

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