Scientific Journal of KubSAU

Automated system-cognitive analysis (ASC-analysis) for images provides automatic identification of specific characteristics of the given images from the color of the pixels and image edges, the synthesis of generalized images of pictures (classes), identifying the most and the least specific image features for the class, determining values of features of images for their differentiation, deletion low-value characteristics (abstraction) from the model, problem solving for quantitative comparison of specific images with generalized images of classes and generalized images of the classes with each other, and objectives of the study of the simulated subject area by studying its model. The work discusses the new features of the ASC-analysis and its implementing intellectual system called "Eidos" for identifying features of images using their spectral analysis, formation of the generalized spectra of classes, the task of comparison of images of specific objects to classes and classes with each other in their spectra. For the first time, it became possible to form the generalized spectra of classes with weights of the colors according to their degree of specificity and unspecific features for classes, and it is not the intensity of the color in the spectrum, but the amount of information in the color on the linking the object with that color to the class. In fact, there is a question of generalization of spectral analysis by using intelligent cognitive technologies and information theory in the spectral analysis. First, everyone is talking about the fact that spectral lines contain information about which element or substance is included in the object, but no one bothered to count what exactly the amount of information is and then use it to determine the composition of the object pattern recognition methods based on the use of this information. Second, spectral analysis is traditionally used to determine the elemental and molecular composition of the object; we propose to use it not only for that, but also to identify any images. A numerical example has been given

Agronomy systems with good reason can be considered as complex multiparameter natural and technical systems. In these systems, there are numerous and diverse physical, chemical and biological processes. On the one hand, these processes have a significant impact on the performance of these systems. On the other hand, they are extremely difficult to be described in the form of meaningful analytical models based on equations. As a result, the development of meaningful analytical models is associated with a large number of simplifying assumptions that reduce the validity of these models. Usually we consider linear univariate models for agronomic systems, whereas practices are necessary for nonlinear multiparameter models. Thus, we face the problem proposed to be solved by the application of a phenomenological meaningful systemic cognitive models. These models are created using automated system-cognitive analysis (ASC-analysis) using the intellectual system called "Eidos" directly based on empirical data and used for the decision of tasks of forecasting, decision support and research of the modeled subject area. In this case, empirical data can be large, incomplete (fragmented), noisy, presented in different types of measuring scales (nominal, ordinal and numerical) and in different units of measurement. The comparability of the processing of heterogeneous data is ensured by the fact that they are all converted into units of measurement of the amount of information. A numerical example has been given

Main scientific results, which were received in 2007 under creation and investigation of semantic information multi mode, providing as detection of dependence between astro signs and accessory of respondents to generalized social categories as a use of knowledge of these dependences for identification of respondents by these categories are casted in the article. Multi model includes 172 private models on 37 generalized categories and each of categories is presented less than 1000 respondents under general fetch capacity of 20007 respondents. It was applied the method of systemic- cognitive analysis, which is considered as one of the universal variants of decision of thirteen problem of Gilbert in practice ( theoretically this problem has been done in the theorem of A.N. Kolmogorova, which is a generalization of theorem V.I. Arnold ( 1957) under it.

Since there are many alternatives to artificial intelligence systems, there is a need of assessment of the quality of mathematical models and systems of artificial intelligence that support these models. This work is aimed at studying and developing standard methods of using the database of UCI repository to assess the quality of mathematical models of systems of artificial intelligence. The aim of this work is the development of methods for assessment of the quality of mathematical models of artificial intelligence systems for the classification of animals by external evidence-based database of the UCI repository. The objectives are: systematization, consolidation and expansion of theoretical and practical knowledge in the discipline of Intellectual information systems and technologies; study of "Eidos" intelligent information system; solving the task with the use of "Eidos" intelligent information systems. The object of research is the "zoo" database of UCI repository. In the first Chapter there is an overview of the theory to the solution of the problem, identification of problems, the original data, tools and metrization scales. In the second Chapter of the work we present the solution of the task. In the conclusion, the results of the work have been made; the conclusions on the achievement of goals and objectives have been given

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 present a solution of the problem of identifying classes of salary levels of employees depending 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 artificial intelligence of UCI repository. In this work we used the database called "Wine Data Set" from the Bank's original task of artificial intelligence from repository UCI. The most reliable in this application was the model of the INF4 based on semantic, according to A. Kharkevich, integral criteria of "Amount of knowledge". The accuracy of the model is 0,916, 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 the system of "Eidos" we used the F-criterion of van Ritbergen and fuzzy multiCLASS generalization proposed by Professor E. V. Lutsenko (L-measure)

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

The quality of life of the population of the region is an important integral criterion of estimation of efficiency of activity of regional administration. Quality of life is mostly influenced by environmental factors. This article proposes to solve the problem of research of the influence of environmental factors on various aspects of quality of life by using ASC-analysis

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

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 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