Abstract
Currently, large industrial enterprises, as well as engineering equipment manufacturers, are successfully integrating the latest achievements in the field of artificial intelligence into the production process to solve various diagnostic and control problems. However, the production environment does not allow the widespread use of artificial intelligence due to the complexities of real-time equipment operation, as well as the large flow of production information. Increased requirements for the fault tolerance of systems, as well as the safety of employees at the enterprise, impose their own restrictions on the use of artificial intelligence algorithms when working with microprocessor technology. To solve such problems, an intelligent technology has been developed based on a unified artificial immune system (UAIS), built using the systematization and classification of modified algorithms to solve a wide range of engineering problems using the example of technological processes in the oil and gas industry. The use of UAIS allows to choose the best algorithm for solving the problem and allows to provide an adequate immune response, depending on the features of the equipment and the type of problem being solved. An approach has been developed for multicomponent evaluation of the effectiveness of modified algorithms of artificial immune systems (MAIS) for the construction of UAIS. This procedure allows, based on a priori information about the properties of the modified algorithms, to compose the structure of the UAIS, as well as to select algorithms in accordance with the target and desired properties for solving a specific problem. The application of the procedure for multicomponent evaluation of modified algorithms of artificial immune systems provides automated configuration of UAIS depending on the characteristics of the production environment.