Scientific Journal of KubSAU

In the article, we develop the methodology of strategic planning and management of the holding on the theoretical basis of automated system-cognitive analysis (ASC-analysis). This methodology provides scientific research of any holding by creating and researching its model. The methodology includes both the synthesis, adaptation and verification of system-cognitive models of the holding, and the use of these models for strategic planning and decision support for managing the holding, as a complex, multiparametric, nonlinear system. The relevance of the research is due to the special role of holdings and other corporate integrated structures both in Russia as a whole and, in particular, in the Krasnodar region. Despite obvious system advantages, holdings face a wide range of problems related to management efficiency, ensuring their sustainable functioning, etc. The proposed methodology offers ways to solve these problems and can be successfully applied in holdings and other corporate integrated structures of various regions, volumes and areas of activity, which determines the relevance of the research topic. The level of significance and scientific novelty of the Research consists in the development of conceptual and theoretical and methodological provisions aimed at managing the development of holdings. The expected results and their significance are that the methodology developed as a result of the Research can be applied by holding companies and other corporate integrated structures and will significantly improve the quality of their management

This work continues the series of works written by the author on the application of modern scientific methods in the study of human consciousness. In 1979-1981, two monographs were written devoted to higher forms of consciousness, the prospects of man, technology and society. One of these monographs was two-volume and was called "Theoretical Foundations of the Synthesis of Quasi-Biological Robots." In these monographs the author proposed: 1) criterial periodic classification of 49 forms of consciousness, including higher forms of consciousness (HFC); 2) based on this classification, there were psychological, microsocial and technological methods of transition between various forms of consciousness, including methods of transition from the usual form of consciousness to the HFC; 3) information-functional theory of the development of technology (including the rule of improving the quality of the basis); 4) information theory of value; 5) 11 functional schemes of technical systems of future forms of society, including remote telekinetic (mental) control systems; 6) the concept of development of society in groups of socio-economic formations; 7) the concept of determining the form of human consciousness by the functional level of the technological environment; 8) mathematical and numerical modeling of the dynamics of the probability density of states of human consciousness in evolution using the theory of Markov’s random processes. In this study, we carry out a complete automated system-cognitive analysis (ASC- analysis) of the periodic criteria classification of forms of consciousness proposed by the author in 1978. To this end, the following tasks are solved in the work: cognitive structuring and formalization of the subject area; synthesis and verification of statistical and system-cognitive models (multi-parameter typification of forms of consciousness); systemic identification of forms of consciousness; their typological analysis; investigations of a simulated domain by examining its model. We have also given a detailed numerical example of solving all these problems

Traditionally, control decisions are made by solving repeatedly the forecasting problem for different values of control factors and choosing a combination of them that ensures the transfer of the control object to the target state. However, real control objects are affected by hundreds or thousands of control factors, each of which can have dozens of values. A complete search of all possible combinations of values of control factors leads to the need to solve the problem of forecasting tens or hundreds of thousands or even millions of times to make a single decision, and this is completely unacceptable in practice. Therefore, we need a decision-making method that does not require significant computing resources. Thus, there is a contradiction between the actual and the desired, a contradiction between them, which is the problem to be solved in the work. In this work, we propose a developed algorithm for decision-making by solving the inverse forecasting problem once (automated SWOT analysis), using the results of cluster-constructive analysis of the target states of the control object and the values of factors and a single solution of the forecasting problem. This determines the relevance of the topic. The purpose of the work is to solve the problem. By decomposing the goal, we have formulated the following tasks, which are the stages of achieving the goal: cognitive-target structuring of the subject area; formalization of the subject area (development of classification and descriptive scales and gradations and formation of a training sample); synthesis, verification and increasing the reliability of the model of the control object; forecasting, decision-making and research of the control object by studying its model. The study uses the automated system-cognitive analysis and its software tools (the intelligent system called "Eidos") as a method for solving the set tasks. As a result of the work, we propose a developed decision-making algorithm, which is applicable in intelligent control systems. The main conclusion of the work is that the proposed approach has successfully solved the problem