name
Lutsenko Yevgeniy Veniaminovich
Scholastic degree
•
Academic rank
professor
Honorary rank
—
Organization, job position
• Kuban State Agrarian University
кафедра компьютерных технологий и систем
профессор
Research interests
Системнокогнитивный анализ, системы искусственного интеллекта, высшие формы сознания, перспективы человека, технологии и общества
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TOP5 coauthors
Articles count: 260
Сформировать список работ, опубликованных в Научном журнале КубГАУ

Description
Automated systemcognitive analysis (ASCanalysis) 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 lowvalue 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 ASCanalysis 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

Description
The automatized algorithm, supplying the resynthesis of models of active object of management under its forwarding the point of bifurcation, allowing to determine the content of classes after qualitative change of purposeful and taking decision object of management is described in this article at the first time.

AGGLOMERATIVE COGNITIVE CLUSTERING OF NOSOLOGICAL IMAGES IN VETERINARY MEDICINE
06.02.00 Veterinary and Husbandry
DescriptionThe article deals with the similarity and difference of nosological images in veterinary medicine using a new method of agglomerative clustering implemented in Automated systemcognitive analysis (ASCanalysis) on a small numerical example. This method is called Agglomerative cognitive clustering. This method differs from the known traditional facts: a) parameters of a generalized image of the cluster are computed not as averages from the original objects (classes) or their center of gravity, and are defined using the same underlying cognitive operations of ASCanalysis, which is used for the formation of generalized images of the classes on the basis of examples of objects and which is really correct and provides a synthesis; b) as a criterion of similarity we do not use Euclidean distance or its variants, and the integral criterion of nonmetric nature: "the total amount of information", the use of which is theoretically correct and gives good results in nonorthonormal spaces, which are usually found in practice; c) cluster analysis is not based on the original variables, matrices of frequency or a matrix of similarities (differences) dependent on the measurement units of the axes, and in the cognitive space in which all the axes (descriptive scales) use the same unit of measurement: the quantity of information, and therefore, the clustering results do not depend on the original units of measurement features. All this makes it possible to obtain clustering results that are understandable to specialists and can be interpreted in a meaningful way that is in line with experts' assessments, their experience and intuitive expectations, which is often a problem for classical clustering methods

AGGLOMERATIVE COGNITIVE CLUSTERING OF SYMPTOMS AND SYNDROMES IN VETERINARY MEDICINE
06.02.00 Veterinary and Husbandry
DescriptionIn the article, on a small numerical example, we consider the similarity and difference of symptoms and syndromes according to their diagnostic meaning, i.e. according to the information they contain about the belonging of conditionals of animals to different nosological images. This problem can be solved for veterinary with the use of a new method of agglomerative cognitive clustering, implemented in Automated SystemCognitive analysis (ASCanalysis). This method of clustering differs from the known traditional methods in: a) in this method, the parameters of the generalized image of the cluster are calculated not as averages from the original objects (symptoms) or their center of gravity, but are determined using the same basic cognitive operation of ASCanalysis, which is used to form generalized images of the classes based on examples of objects and which really correctly provides a generalization; b) the similarity criterion is not the Euclidean distance or its variants, but the integral criterion of nonmetric nature: "the total amount of information", the application of which is theoretically correct and gives good results in unortonormated spaces, which are usually found in practice; c) cluster analysis is carried out not on the basis of initial variables, frequency matrices or matrix of similarity (differences), depending on the units of measurement on the axes (measurement scales), but in cognitive space, in which one unit of measurement is used for all axes: the amount of information, and therefore the results of clustering do not depend on the initial units of measurement of features of objects. All this allows us to get the results of clustering, understandable to specialists and amenable to meaningful interpretation, wellconsistent with the experts ' assessments, their experience and intuitive expectations, which is often a problem for classical clustering methods

01.00.00 Physicalmathematical sciences
DescriptionClassical combinatorial formula to calculate the number of combinations from n on m: C(n,m)=n!/(m!(nm)!) involves the intermediate calculation of factorials, which is often impossible when n>170, due to limitations in the capacity of numbers that are used in programming languages and created through these systems. However, in some cases it is necessary to calculate the number of combinations for n and m much larger than this limit, such as when a value greater than 10000. In such cases, there is a definite problem, which manifests itself, for example in the fact that many online services meant to calculate the number of combinations with these parameters do not work properly. In this article, we present its solution in the form of an algorithm and software implementation. The essence of the approach is to first decompose the factorials into prime factors and reduce them, and then to produce multiplication. This approach differs from those cited in the Internet

THE ASYMPTOTIC INFORMATION CRITERION OF NOISE QUALITY
DescriptionIntuitively everyone understands that noise is a signal in which there no information is, or which in practice fails to reveal the information. More precisely, it is clear that a certain sequence of elements (the number) the more is the noise, the less information is contained in the values of some elements on the values of others. It is even stranger, that noone has suggested the way, but even the idea of measuring the amount of information in some fragments of signal of other fragments and its use as a criterion for assessing the degree of closeness of the signal to the noise. The authors propose the asymptotic information criterion of the quality of noise, and the method, technology and methodology of its application in practice. As a method of application of the asymptotic information criterion of noise quality, we offer, in practice, the automated systemcognitive analysis (ASCanalysis), and as a technology and software tools of ASCanalysis we offer the universal cognitive analytical system called "Eidos". As a method, we propose a technique of creating applications in the system, as well as their use for solving problems of identification, prediction, decision making and research the subject area by examining its model. We present an illustrative numerical example showing the ideas presented and demonstrating the efficiency of the proposed asymptotic information criterion of the quality of the noise, and the method, technology and methodology of its application in practice

01.00.00 Physicalmathematical sciences
DescriptionWithout 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 largescale 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 systemcognitive 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

ASCANALYSIS OF THE DEPENDENCE OF PAYMENTS TO EMPLOYEES OF AIC FROM THEIR CHARACTERISTICS
DescriptionThe 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/gotovyetablitsyexcelbesplatno. 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 ACSanalysis and the system called "Eidos" we have used Fcriterion of van Ritbergen and fuzzy multiclass generalization proposed by Professor E. V. Lutsenko

Description
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

СSCANALYSIS AS THE ADEQUATE INSTRUMENT OF CONTROLLING AND MANAGEMENT FOR MEDIAL AND SMALL FIRM
DescriptionIn the article, it is demonstrated that for the present stage of evolution of controlling its increasing infiltration into averages and small firms is typical. Thus, there is a problem to discover uniform, simple in assimilation and the inexpensive toolkit of the control unitensuring making of intellectual procedures for management on various hierarchy levels of control of company. Demands to control unit tooling are justified; it is demonstrated that to the formulated demands there matches a method of the computerized systemcognitive analysis and its tooling – "Eidos"system. Instances of application of the yielded tooling for the problem of quality management of preparation of specialists, information security, determination of the nomenclature and volume of the implementable goods, a basic technology and staff management selection are shown