Scientific Journal of KubSAU

The article describes the synthesis and verification of statistical and system-cognitive models of the influence of environmental factors on the quality of life of the population of the region. This stage of the ASC-analysis is performed in the system called "Eidos". As a result, we have created and validated (verification stage) all the specified systemic cognitive models. It is expected that reliability for the models of knowledge is sufficiently high for a given subject area, that is why we can state the discovery of a dependence of life expectancy and causes of death from environmental conditions. Typically, knowledge models are approximately 20% higher in accuracy than statistical models, which operate on the principle of positive pseudo-prediction. Making decisions based on the model of Abs (matrix of absolute frequencies) is not appropriate because of the different number of instances of classes (generalized categories) and dependence of the solutions of this amount. In the model called Prc2 (conditional and unconditional percentage distribution) the dependence of the model values of the number of examples in classes has been removed, but the accuracy of it is usually same low as in the Abs. In addition, for decision-making based on this model, one has to compare the values of conditional and unconditional probabilities manually, which is laborious and hardly possible for large dimensional models. The knowledge model called Inf3, based on a measure similar to the Chi-square, is the result of the automated comparison of values of conditional and unconditional probabilities presented in the model of Prc1, which is similar to Prc2, and usually has a fairly high accuracy, especially considering the high complexity of the subject area, which we simulated. Therefore, in accordance with the technology of the ASC-analysis data conversion into information, and afterwards - into knowledge, it is the model of Inf3 which is planned to be used for the solution of problems of identification, forecasting, decision-making and exploring the modeled subject area, through the study of its models

Without science it would be impossible to form a full environmental consciousness. To increase the validity and weight of the findings on the impact of environment on quality of life, it is necessary to quantify the strength and direction of the influence of diverse environmental factors. However, it appears that this is quite problematic for a number of reasons. First, it is the lack or inaccessibility of source of data which is necessary for such type of research. The same data, which still can be found cover just small periods of observations (small longitudinal research data), and their completion, including performing experiments, is fundamentally impossible. As a result, it is impossible to require such full data replications, which is a necessary condition for correct applying of factor analysis. Secondly, environmental factors are described with heterogeneous indices measured in different types of measurement scales (nominal, ordinal and numerical) and in different measurement units. Mathematical methods of comparable processing of such data, and the right software tools for these methods, generally speaking, do not exist. Third, these tasks are large-scale problems, i.e. they are not talking about 5 or max 7 factors as it was in factor analysis, but about hundreds and thousands. Fourthly, the original data is noisy and require sustainable methods. Fifthly, environmental factors are interrelated and require nonlinear nonparametric approaches. To solve these problems it is proposed to apply a new innovative intelligent technology: automated system-cognitive analysis and its software tool – a system called "Eidos". We have also given a brief numerical example of assessing the impact of environmental factors on life expectancy and causes of death

In the article, the problem of agribusiness industry control is stated, the purposes of control and measure of its success, and also composition of the computerised management system, including control object, controlling system, informational-measuring system and also a subsystem of rendering of corrective actions are considered. What is offered: 1) the control purpose is to consider a raise of quality level of life of the population of region; 2) the capacity of measure of success of control is to consider indexes of quality level of life of the population; 3) numbers and direction of investments can be used as the controlling factor; 4) synthesis and verification of model of agrarian and industrial complex can be performed directly in a cycle of control, based on application of system-cognitive analisys (SC-analisis) and its programmatic tooling - "Eidos" intellectual system; 5) forecasting of evolution of agrarian and industrial complex and production of controlling solutions can be performed on the basis of cognitive model of agrarian and industrial complex with SC-analisis and application of "Eidos" system

In this article, in accordance with the methodology of SC analysis, we consider particular implementation stages of the synthesis of the numerical model and its analysis. We have also presented the results of the determination of the different states of the processing complex function of various factors on these states and their classification, as well as semantic networks and cognitive class diagrams and factors. On the basis of the analysis we made specific findings and recommendations for decision making at the management level of the region. After execution of the stages of cognitive structuring and formalization of the subject area the further stages of automated SC analysis have been accomplished, the first of which is the phase of the input database of precedents. All these steps are performed directly using "Eidos" universal cognitive analytical system

The article deals with the use of intelligent technology "Aidos" for the prevention of fires, electrical injuries, and accidents at agricultural sector and optimizing the security measures of human-machine systems. Causes of accidents are multi-phase or single-phase short-circuit in the supply network or electrical installation, the failure of the primary protective equipment and violations of regimes for electrical installations, causing overloads, deterioration of the insulation of supply cables, the mismatch of protective devices to regulatory requirements. Implementation of systemcognitive analysis provides a reduction in the number of dangerous fabricated experiences at hazardous production facilities. Due to the application of ASCanalysis, it provides a more efficient operation of electric installations on dangerous industrial objects, which means to prevent fires, electric shock injuries, accidents and optimize the safety measures for manmachine systems. Users of the system called "Eidos" may be companies with a high risk of appearance of the accidents at hazardous production objects: agroindustrial complex, gas supply, heat and electricity, oil-processing components, metallurgical industry, chemical, petrochemical and oil industry, main pipelines-wire transport, food and oil industry and others. Planned efficiency and effectiveness of the implementation of ASC-analysis is provided by reducing the number of dangerous man-made situations: accidents, fires, and electrocution on dangerous production units-projects. The implementation of ASCanalysis allows to increase city efficiency of forecasting of the technical condition of the power plant and to determine its residual lif

In this article, in accordance with the methodology of the Automated system-cognitive analysis (ASCanalysis), we examine the implementation of the 1st and 2nd stages of ASC-analysis: cognitive structuring and formalization of the subject area. At the stage of cognitive structurization of subject area, researchers decide what to consider as the object of modeling, the factors affecting it and the results of their actions. In accordance with the results of the cognitive structurization, we prepare the initial database for the study (training sample or case-based reasoning). At the stage of formalization of the subject area, the base of the original data is being normalized, i.e., we develop classification and description: the scale and graduations and with their use the base of the source data is being encoded. The result is a database of events (eventological database) and the training sample. The stage of cognitive structuring and preparation of the source data is not formalized and the formalization of the subject area is fully automated and performed directly with the use of the universal cognitive analytical system named "Eidos", which is a software Toolkit for ASC-analysis. Stages of cognitive structurization and formalization of the subject area of ASC-analysis are the first steps of data conversion into information and into knowledge. Subsequent steps: the synthesis and verification of system-cognitive model, the decision of problems of identification, forecasting and decision making, as well as studies of the modeled object by studying its model will be considered in future articles

In this article, the routine of synthesis of four models of the corporation, different by frequent measure of correlation between past indexes of the factories entering into corporation and the future statuses of corporation as a whole is featured, verification of all private models with utilization of two integral measure is fabricated, forecasting of the future statuses of corporation on their system of determination is performed

In this article, the authors have conducted a survey of the system-cognitive model for forecasting and support of decision-making of the choice of agricultural technologies in the production of grain, providing the desired economic, energetic, financial and economic results with high probability

The article proposes using the automated system-cognitive analysis (ASC-analysis) and its software tool, which is the system called "Eidos" for synthesis and application of adaptive intelligent measuring systems to measure values of parameters of objects, and for system state identification of complex multivariable nonlinear dynamic systems. The article briefly describes the mathematical method of ASC-analysis, implemented in the software tool – universal cognitive analytical system named "Eidos-X++". The mathematical method of ASC-analysis is based on system theory of information (STI) which was created in the conditions of implementation of program ideas of generalizations of all the concepts of mathematics, in particularly, the information theory based on the set theory, through a total replacement of the concept of “many” with the more general concept of system and detailed tracking of all the consequences of this replacement. Due to the mathematical method, which is the basis of ASC-analysis, this method is nonparametric and allows you to process comparably tens and hundreds of thousands of gradations of factors and future conditions of the control object (class) in incomplete (fragmented), noisy data numeric and non-numeric nature which are measured in different units of measurement. We provide a detailed numerical example of the application of ASC-analysis and the system of "Eidos-X++" as a synthesis of systemic-cognitive model, providing a multiparameter typization of the states of complex systems, and system identification of their states, as well as for making decisions about managing the impact of changing the composition of the control object to get its quality (level of consistency) maximally increased at minimum cost. For a numerical example of a complex system we have selected the team of the company, and its component – employees and applicants (staff). However, it must be noted that this example should be considered even wider, because the ASC-analysis and the "Eidos" system were developed and implemented in a very generalized statement, not dependent on the subject area, and can successfully be applied in other areas

In this article, for the first time, the synthesis and veri-fication of the system-cognitive model of artificial ecosystems of sunflower crops in the Krasnodar region (at the levels of regions and in the whole region) are carried out. On the basis of the developed models, there are solved tasks: 1. Forecasting scenario of sun-flower yield for the period from 1 to 5 years. 2. The scientific study of artificial ecosystems of sunflower crops in the Krasnodar region (at the levels of regions and in the whole region)