2018 IEEE Northwest Russia Conference on Mathematical Methods in Engineering and Technology (ММET NW)

1 / 2018-03-19 03:00:58

Artificially immune system with using of fuzzy logic for optimal reply

mathematical model of artificial immune system; fuzzy logic; optimal reply

This article deals with the development of artificially immune system with using of fuzzy logic for optimal control systems. At present, the immune system is considered by researchers as a source of ideas and methods for solving various tasks in the field of information processing and analysis, mathematical modeling and information security. The immune system is a structure in which the mechanisms implemented learning, memory, and associative search to solve the problems of recognition and classification. The immune system is of great interest due to its important role in maintaining the integrity of the organism. The properties of the immune system are a remarkable example of local adaptive processes that implement an effective global response. Is expanding the scope of application of new methods for solving applied problems, based on the principles of immunology.
In this article the adequate mathematical model of artificial immune system with using of fuzzy logic is investigated. In the article was developed a mathematical model describing the organism response to medicines in the process of infection used to develop the optimal dynamics of the number of infected and cured cells depending on the relative initial conditions and the appropriate therapeutic dose, based on fuzzy logic methods. For the parameters of the mathematical immune model of the organism reactions to medicines there were generated fuzzy scenarios of infection extension in the organism, according to the forms of organism infection and to the therapeutic doses of medicines: fuzzy set of cascading changes in the number of detected and cured cells, fuzzy set of therapeutic doses of medicines.