Abstract
This study provides information on artificial immune systems. The artificial
immune system is an adaptive computational system that uses models,
principles, mechanisms and functions to describe and solve the problems in
theoretical immunology. Its application in various fields of science is explored.
The theory of natural immune systems and the key features and algorithms of
artificial immune system are analyzed. The advantages and disadvantages of
protection systems based on artificial immune systems are shown. The methods
for malicious software detection are studied. Some works in the field of artificial
immune systems are analyzed, and the problems to be solved are identified.
A new algorithm is developed for the application of Bayesian method in
software using artificial immune systems, and experiments are implemented.
The results of the experiment are estimated to be good. The advantages and
disadvantages of AIS were shown. To eliminate the disadvantages, perfect
AISs should be developed to enable the software more efficient and effective.
Artificial Immune Systems for Solving the Uncapacitated Single-Allocation p-Hub Median Problem
