Development of a cognitive mnemonic scheme for an optical Smart-technology of remote learning based of Artificial Immune Systems

Abstract

The article discusses current issues related to the development of an information optical Smart technology for distance learning of Honeywell's distributed Experion PKS control system for the oil and gas industry. About 70 % of industrial accidents are caused by the human factor through the fault of operators. The work of operators consists in monitoring and managing high-tech proc-esses through mnemonic scheme circuits and is characterized by increased tension in the visual apparatus, as well as general fatigue and loss of concentration. The innovative personalized tech-nology of distance learning takes into account the peculiarities of students' vision by adjusting the color supply of educational material and the dynamic presentation of information depending on the person's psychotype and is based on the use of cognitive, optical, multi-agent technologies, as well as ontological and immuno-network approaches. The development of cognitive mnemonic schemes is carried out taking into account these features, which allows one to reduce the load on the visual apparatus and increase the effectiveness of teaching practical skills when working with mnemonic schemes. An artificial immune systems approach is used to predict and evaluate the learning process and promptly adjust the knowledge obtaining process. A modified algorithm for the functioning of a distance learning system based on the use of optimization algorithms for arti-ficial intelligence and an algorithm for immuno-network modeling has been developed. General principles of creating mimic diagrams and existing Honeywell mnemonic schemes are considered. An example of the implementation of the proposed remote technology is presented and results of the simulation of cognitive mnemonic scheme for various categories of students with special needs are discussed.