
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
Системно-когнитивный анализ, системы искусственного интеллекта, высшие формы сознания, перспективы человека, технологии и общества
Web site url
Current rating (overall rating of articles)
0
TOP5 co-authors
Articles count: 271
Сформировать список работ, опубликованных в Научном журнале КубГАУ
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01.00.00 Physical-mathematical sciences
Description
The creation of artificial intelligence systems is one of important and perspective directions of development of modern information technology. Since there are many alternatives of mathematical models of systems of artificial intelligence, there is a need to assess the quality of these models, which requires their comparison. To achieve this goal we require free access to the source data and methodology, which allows to convert these data into a form needed for processing in artificial intelligence. A good choice for these purposes is a database of test problems for systems of artificial intelligence of repository of UCI. In this work we used the database "Iris Data Set" from the bank's original task of artificial intelligence – UCI repository, which solved the problem of formalization of the subject area (development of classification and descriptive dials and graduations and the encoding of the source data, resulting training sample, essentially representing a normalized source data), synthesis and verification statistical and system-cognitive models of the subject area, identify colors with classes, which serve varieties of Iris, as well as studies of the subject area by studying its model. To solve these problems we used the automated system-cognitive analysis (ASC-analysis) and its programmatic Toolkit – intellectual system called "Eidos"
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01.00.00 Physical-mathematical sciences
Description
The article discusses the application of automated system-cognitive analysis (ASC-analysis), its mathematical model which is system theory of information and its software tool, which is intellectual system called "Eidos" for solving problems related to identification of types and models of aircraft by their silhouettes on the ground, to be more precise, their external contours: 1) digitization of scanned images of aircraft and creation of their mathematical models; 2) formation of mathematical models of specific aircraft with the use of the information theory; 3) modeling of the generalized images of various aircraft types and models and their graphic visualization; 4) comparing an image of a particular plane with generalized images of various aircraft types and models, and quantifying the degree of similarities and differences between them, i.e., the identification of the type and model of airplane by its silhouette (contour) on the ground; 5) quantification of the similarities and differences of the generalized images of the planes with each other, i.e., clusterconstructive analysis of generalized images of various aircraft types and models. The article gives a new approach to digitizing images of aircraft, based on the use of the polar coordinate system, the center of gravity of the image and its external contour. Before digitizing images, we may use their transformation, standardizing the position of the images, their sizes (resolution, distance) and the angle of rotation (angle) in three dimensions. Therefore, the results of digitization and ASC-analysis of the images can be invariant (independent) relative to their position, dimensions and turns. The shape of the contour of a particular aircraft is considered as a noise information on the type and model of aircraft, including information about the true shape of the aircraft type and its model (clean signal) and noise, which distort the real shape, due to noise influences, both of the means of countering detection and identification, and environment. Software tool of ASC-analysis, i.e. Eidos intellectual system, provides identification of the type and the model of airplane by its silhouette, as it was shown in a simplified numerical example
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01.00.00 Physical-mathematical sciences
Description
Classic quantitative measure of the reliability of the models: F-measure by van Rijsbergen is based on counting the total number of correctly and incorrectly classified and not classified objects in the training sample. In multiclass classification systems, the facility can simultaneously apply to multiple classes. Accordingly, when the synthesis of the model description is used for formation of generalized images of many of the classes it belongs to. When using the model for classification, it is determined by the degree of similarity or divergence of the object with all classes, and a true-positive decision may be the membership of the object to several classes. The result of this classification may be that the object is not just rightly or wrongly relates or does not relate to different classes, both in the classical F-measure, but rightly or wrongly relates or does not relate to them in varying degrees. However, the classic F-measure does not count the fact that the object may in fact simultaneously belongs to multiple classes (multicrossover) and the fact that the classification result can be obtained with a different degree of similarity-differences of object classes (blurring). In the numerical example, the author states that with true-positive and true-negative decisions, the module similarities-differences of the object classes are much higher than for false-positive and false-negative decisions. It would therefore be rational to the extent that the reliability of the model to take into account not just the fact of true or false positive or negative decisions, but also to take into account the degree of confidence of the classifier in these decisions. In classifying big data we have revealed a large number of false-positive decisions with a low level of similarity, which, however, in total, contribute to reducing the reliability of the model. To overcome this problem, we propose a L2-measure, in which instead of the sum of levels of similarity we use the average similarity by different classifications. Thus, this work offers measures of the reliability of the models, called L1-measure and the L2 measure, mitigating and overcoming the shortcomings of the F-measures; these measures are described mathematically and their application is demonstrated on a simple numerical example. In the intellectual system called "Eidos", which is a software toolkit for the automated system-cognitive analysis (ASC-analysis), we have implemented all these measures of the reliability of the models: F, L1 and L2
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INVESTMENT AND RESOURCE MANAGEMENT OF AGRICULTURAL PRODUCTION
Description
In the article, we proposed the fundamental mathematical support of the state investment management of the agricultural production at the regional level, the content of which is determined by the next run of the development: the structure of the investment mechanism of farm management, hierarchy and relationship models and stages of the investment management of agricultural production; models preliminary comparative evaluation of agricultural enterprises - participants of the investment process, models and algorithms investment and resource optimization of the industrial structure of agricultural enterprises; models final selection of participants implementation of public investment programs and the distribution of funds
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Description
The problem of forming of innovate elements of intelligence service of corporate management is dis-cussed on terms of knowledge economics. New trends and conditions of corporation’s development as reflection of economics trends are picked out. The system of measures pointed at stimulation of producing of future intelligence foundation and me-chanisms of such producing are suggested
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Description
In the article the intellectual consulting system providing revealing of technological knowledge by systemic-cognitive analysis of business processes, and also decision-making support on effective application of this knowledge for the purpose of achievement of the set indicators economic-economic efficiency is described. The detailed numerical example of application of system on the basis real data of one of the Kuban firms for revealing of technological knowledge on cultivation of a winter wheat and application of this knowledge for decision-making support for choice of the definite agrotechnology, providing desirable indicators of productivity of a winter wheat, its quality, and also profit and profitability is resulted. It is offered to apply evident multilayered graphic cartographical visualization of results of forecasting of productivity of culture (and grades), qualities, profit and profitability on firm fields
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01.00.00 Physical-mathematical sciences
Description
Adequate and effective assessment of the efficiency, effectiveness and quality of scientific activities of specific scientists and research teams is crucial for the information society and society based on knowledge. The solution to this problem is the subject of scientometrics and its purpose. The current stage of development scientometrics differs greatly from its previous appearance in the open as well as paid on-line access to huge amount of detailed data on a large number of indicators on individual authors and on scientific organizations and universities. In the world, there are well-known bibliographic databases: Web of Science, Scopus, Astrophysics Data System, PubMed, MathSciNet, zbMATH, Chemical Abstracts, Springer, Agris, or GeoRef. In Russia, it is primarily the Russian scientific citing index (RSCI). RSCI is a national information-analytical system, accumulating more than 9 million publications of Russian scientists, as well as information about citation of these publications from more than 6,000 Russian journals. There is a lot of data, so-called "Big data". The main primary scientometric indicator (based on which we build all the rest, such as the h-index) is the number of citations of the author's works, placed in the bibliographic database. This number of citations is determined by the software of RSCI using so-called "binding" which is a grammatical analysis and search in databases for works of the author, for relevant links from references in the works of various authors. However, the problem is, as experience shows, that authors make a very large number of simply incorrect and incomplete references in the reference lists, very far from standard. Currently, the software that RSCI uses does not automatically bind these invalid references, and this requires human intervention. But, centrally, to do this is not possible by experts of RSCI because of the huge amount of work, and distributed work for a large number of specialists in the field still requires a centralized moderation. As a result, the work for binding references to the literary sources is very slow and a huge amount of links is unbound. This leads to an underestimation of nanomatrices indicators of both individual authors and research teams that cannot be considered acceptable. The solution to this problem is offered by applying the automated system-cognitive analysis (ASC-analysis) and its programmatic Toolkit – intellectual system called "Eidos". This work provides a numerical example of the intellectual anchor of the real incorrect references to the works of the author on the basis of a small amount of real scientific data that are publicly available free on-line access to the RSCI
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Description
In the article the technology and some results of application of systemic-cognitive analysis for revealing of knowledge of consequences of errors in configuration of safety systems under report of Microsoft Baseline Security Analyzer (MBSA) and uses of this knowledge for forecasting of consequences are described
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01.00.00 Physical-mathematical sciences
Description
The quality of a system is seen as an emergent property of systems, due to their composition and structure, and it reflects their functionality, reliability and cost. Therefore, when we speak about quality management, the purpose of management is the formation of pre-defined system properties of the object of management. The stronger the object of the control expresses its system properties, the stronger the nonlinearity manifests of the object: both the dependence of the management factors from each other, and the dependence of the results of the action of some factors from the actions of others. Therefore, the problem of quality management is that in the management process the management object itself changes qualitatively, i.e. it changes its level of consistency, the degree of determinism and the transfer function itself. This problem can be viewed as several tasks: First is the system identification of the condition of the object of management, 2nd – making decisions about controlling influence that changes the composition of the control object in a way its quality maximally increases at minimum costs. To solve the 2nd problem we have proposed an application of the component selection of the object by functions based on the resources allocated for the implementation of different functions; costs associated with the choice of the components and the degree of compliance of various components to their functional purpose. In fact, we have proposed a formulation and a solution of the new generalization of a variant of the assignment problem: "multi backpack", which differs from the known with the fact that the selection has been based not only on the resources and costs, but also with taking into account the degree of compliance of the components to their functional purpose. A mathematical model, which provides a solution to the 1st problem, and reflecting the degree of compliance of the components to their functionality, as well as the entire decision-making process for selections, i.e. 2nd task, has been implemented in the ASC-analysis and in the system called "Eidos" X++". The article also provides a simplified numerical example of the proposed approach with the selection of staff members
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INTELLECTUAL MANAGEMENT OF THE NOMENCLATURE AND REALIZATION VOLUMES IN A TRADING COMPANY
Description
In the article the technology of application of systemic-cognitive analysis for creation a real trading firm on the basis of data and application of a technique of forecasting and decision-making support at such choice of the nomenclature and volumes of realised production which provide reception of the maximum profit and profitability in it is described