Scientific Journal of KubSAU

Is it possible to automate the study of the properties of numbers and their relationship so that the results of this study can be formulated in the form of statements, indicating the specific quantity of information stored in them? To answer this question it is offered to apply the same method that is widely tested and proved in studies of real objects and their relations in various fields to study the properties of numbers in the theory of numbers namely - the automated system-cognitive analysis (A.S.C. analysis), based on information theory

In this article, the deep relationship between the theory of automated control and system-cognitive analysis and its software tools - system of "Eidos" in their application to the intelligent control of complex systems is reviewed. Offered technology allows implementing in practice the intelligent automated and even automatic control of the objects of management, for which earlier management is realized only on weak formalized level, as a rule, without the use of mathematical models and computers. Such control objects include, for example, technical systems, the full quality-changing in the process of management, biological and ecological systems, socio-economic and psychological systems

A determination system of the population health is a big complex hierarchical system. The current level of management of such systems involves the use of mathematical models and corresponding software tools for the accumulation of baseline data (monitoring), identification, prediction and decision-making. However, when modeling such large complex systems, we face a number of problems. The main problem is that in one model it is necessary to process a very large number of factors in a proper and comparable way, that are measured in different units, and different types of scales (numeric and text). Traditionally, to solve this problem and determine the values of individual criteria we use expert evaluation and desirability functions, and the integral criterion is the geometric mean. However, the traditional approach, currently applied in this field, has several disadvantages. First, in the traditional model it is defined in an expert way, which factors influence the decision of different problems in a positive way, which ones are negative and which ones do not affect. Second, for the numerical evaluation of influence factors on the solution of the problem we use different algorithms for calculating values of the desirability function for positively and negatively influencing factors which, when used as an integral criterion of the geometric average, leads to comparable results. Third, the use of normalized utility functions leads to the leveling force of the impact factors resulting in weak impact and the influencing factors are given the same variation in numeric values and have similar influence on integral criteria. All of the mentioned problems of the traditional approach have been resolved using Automated system-cognitive analysis (ASC-analysis) and its programmatic Toolkit – Universal cognitive analytical system called "Eidos". In the proposed systemic cognitive model, for the values of environmental and economic factors, without the participation of the experts, we have calculated the amount and the sign of the information contained there about some values of indicators of population health

It is well known that genetics studies the mechanisms of variation/heredity and widely uses the concept of "genetic information". While genetics considers the information as the content of the genetic code - structure of DNA and RNA included in the cell of a living organism. Genetics examines the mechanisms of recording, copying, readout of genetic information, the possibility of its modification and its influence on the characteristics and properties of the organism. In conversational and scientific language we know phrases, such as "Genes contain information about the characteristics/properties of the body." Paradoxically, we see no attempts to determine the amount of information contained in specific genes on specific characteristics or phenotypic properties of the organism. It would seem that the application of information theory in genetics is a completely natural and suggests itself. More strange that there are practically no works devoted to the application of information theory for solving problems of genetics. This article is intended, to some extent, to fill this gap on the example of calculating the amount of information in the genes of the characteristics or properties of different grape varieties. It examines the application of automated system-cognitive analysis (ASC-analysis), its mathematical model – system of information theory and software tools – intellectual system called "Eidos" for solving one of the important tasks of genetics: determine the amount of information contained in the genes on various phenotypic characteristics/properties of the grapes. To solve this problem, we perform the following steps: 1) cognitive-targeted structuring of the subject area; 2) the formalization of the subject area, i.e. development of classification and descriptive dials and graduations and training samples; 3) synthesis and verification of information model, reflecting the amount of information in the genes on the phenotypic characteristics/properties (multiparameter typing); 4) displaying the information about the genetic determination system of phenotypic characteristics/properties (SWOT analysis of Fennovoima); 5) displaying the information about the strength and direction of influence of a specific gene on phenotypic characteristics/properties (SWOT-diagrams of genes); 6) the solution to the problem of system identification phenotypic characteristics/properties by the presence of certain genes; 7) quantification of the similarities-differences of the various phenotypic characteristics/properties, upon determination system genes. A specific phenotypic property (or characteristic) is regarded as a noisy genetic text, including genetic information about the true gene property (clean signal) and the noise that distorts this information due to the random effects of the environment. The software tool of the ask-analysis which is "Eidos" intellectual system provides the noise suppression and the selection of true signal

The cognitive simulation of AstroDatabank records by using the Artificial Intelligence System – AIDOS is reviewed in this paper. The technology of simulation is described and the mostly important results are discussed.

Artificial intelligence system “Aids-Astra” for scientific research of global geo-systems depending on astronomical parameters of Solar system celestial bodies is discussed

This article is written in connection with the anniver-sary of 100-th issue of the Scientific journal of Kuban state agrarian University. This event suggests the pos-sibility of studying the dynamics topics of research for publication in the Scientific journal of Kuban state agrarian University. This issue is described in the arti-cle. The instrument for this study was applied auto-mated system-cognitive analysis (ASC-analysis) and software tools - Universal cognitive analytical system "Eidos-X++"

The creation of artificial intelligence systems is one of important and perspective directions of development of modern information technology. As there are many alternatives to artificial intelligence systems, there is a need to evaluate mathematical models of these systems. In this work, we consider a solution of the problem of identifying classes of levels of pay of employees on their characteristics. To achieve this goal, it requires free access to test the source data and methodology, which will help to convert the data into the form needed for work in artificial intelligence systems. A good choice is the databases from the site: http://allexcel.ru/gotovyetablitsy-excel-besplatno. In this work, we have used the database called "The database table of employees, payments calculation". The most reliable in this application was the model of the INF4 based on semantic appropriate measure of information of A. Kharkevich with integral criteria of "Amount of knowledge". The accuracy of the model is 0.960, which is much higher than the reliability of expert evaluations, which is equal to about 70%. To assess the reliability of the models in the ACS-analysis and the system called "Eidos" we have used F-criterion of van Ritbergen and fuzzy multiclass generalization proposed by Professor E. V. Lutsenko

Studying natural phenomena in all their diversity, humanity worked experienced in every field of science the model of perceiving the world and methods of obtaining information. The development of science currently cannot be imagined without research on the intersection of its regions. This article presents the results of the automated systemcognitive analysis of the size of atoms from the main characteristics that are of research at the interface of General chemistry elements and intelligent systems. Dependence of nuclear radius, mass and of the atom and the charge number are identical in shape and size, which is probably connected with the linear increase of these parameters in the Periodic system of chemical elements. There is also a similar form of the dependences of radii of atoms from the factors ex and x, because these factors are interrelated. The obtained results of the ask analysis have confirmed the theoretical assumptions and the formulae of the dependence of main characteristics of the atom

The creation of artificial intelligence systems is one of important and perspective directions of development of modern information technology. As there are many alternatives to artificial intelligence systems, there is a need to evaluate mathematical models of these systems. In this article, we consider a solution of the problem of identifying classes of levels of pay to employees on their characteristics. To achieve this goal it requires free access to test the source data and methodology, which will help to convert the data into the form needed for work in artificial intelligence systems. A good choice is a database of test problems for systems of UCI artificial intelligence repository. In this work we have used data base on teaching effectiveness for three regular semesters and two summer semesters of 151 teaching assistant (TA) assignments at the statistics Department of the University of Wisconsin-Madison. The most reliable in this application was the model of the INF4. The accuracy of the model in accordance with Lmeasure made up 0,809, which is much higher than the reliability of expert evaluations, which is equal to about 70%. To assess the reliability of the models in the ASC-analysis and in the system of "Eidos" we use F-criterion of van Ritbergen and its fuzzy multiclass generalization proposed by Professor E. V. Lutsenko