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: 276
Сформировать список работ, опубликованных в Научном журнале КубГАУ
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08.00.13 Mathematical and instrumental methods of Economics
DescriptionIn previous works, the authors solved the problem of cognitive structuring and formalization of the subject area, synthesis and verification of system-cognitive models, predicting the impact of nomenclature and sales volumes on the profit and profitability of the trading company, decision support for the selection of such nomenclature and sales volumes, which cause a given target profit and profitability of the company. This work is devoted to the study of the simulated subject area by studying its SC-model
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SYSTEM FUZZY INTERVAL MATHEMATICS - A PROMISING AREA OF THEORETICAL AND COMPUTATIONAL MATHEMATICS
01.00.00 Physical-mathematical sciences
DescriptionThe article b riefly considers the prospects of some “points of growth” in the modern theoretical and computational mathematics: the numbers and sets, i.e. the base of modern mathematics; mathematical, pragmatic and computer numbers; from the usual sets - to unclear; the theory of fuzzy sets and “fuzzy dou-bling” of mathematics; the mix of fuzzy set theory to the theory of random sets; interval numbers as a spe-cial case of fuzzy sets; development of interval mathematics (interval doubling of mathematics); the system as a generalization of a multitude; the systematic generalization of mathematics and tasks emerging; the systematic generalization of operations on sets (on the example of the operation of the Boolean association); the systematic generalization of the concept of functions and functional dependencies participation; cognitive function; the matrix of knowledge as fuzziness with an estimated degree of truth of showing data systems arguments on the system of values of the function; modification of the method of least squares for the approximation of cognitive functions; development of the idea of the systematic generalization of mathematics in the field of information theory – system emergent information theory; information measures of the level of consistency; ratios of emergence; direct and opposite, direct and indirect logical reasoning with an estimated level of truth; intellectual system of Eidos X++ as a toolkit that implements the ideas of system of a fuzzy interval sum of mathematics
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Description
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.
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Description
The article proposes to use the automated systemcognitive analysis (ASC-analysis) and its software tool which is "Eidos" system to solving multiparameter typing, system identification and cartographic visualization of spatially-distributed natural, environmental and socio-economic systems. Imagine, that we have an original point cloud with coordinates (X,Y,Z), each with known values of gradation descriptive scales of nominal, ordinal, or numeric type S(s1,s2,...,sn). Then the "Eidos" system provides: 1) building a model that contains generalized knowledge about the strength and the direction of the influence of descriptive gradations of scales at Z=M(S); 2) estimation of the values of Z for points (X,Y) described in the same descriptive scales S(s1,s2,...,sn), but not a part of the original point cloud; 3) a cartographic visualization of the spatial distribution of values of the function Z=M(S) for points outside the initial cloud, using Delaunay triangulation. Basically, this means that the "Eidos" system ensures recovery of the unknown function values on the grounds of the argument and implements it in a generic setting, independent of subject area. We propose a new scientific concept called "Geo-cognition system", which is defined as a software system that provides conversion of source data into information, and knowledge in visualization and mapping of this knowledge, resulting in the cognitive map becomes graphics. This feature can be used to quantify the degree of suitability of the watersheds for cultivation of certain crops, the evaluation of the ecological situation on particular territories on the structure and intensity of anthropogenic load, visualization of results of forecasting of earthquakes and other unwanted risks or emergencies, as well as for solving many other similar mathematical essence of tasks in a variety of subject areas. We have also shown a simple numerical example
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Description
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
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Description
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
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Description
In this article, the authors analyze forecasting and adoption of administrative decisions of a choice of agro technologies by means of application of the method of system-cognitive analysis
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Description
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
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Description
This article at first time presents the synthesis and verification of systemic cognitive model of natural economic system, we have also justified the opportunity of forecasting and decision management, the strategic decisions of the choice of agricultural technologies
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Description
The article basically formulates the problem of effective forecasting of results and acceptance - making on the choice of agricultural technologies to produce the desired result. We have offered and proved the possi-bility of forecasting and management in grain production through the application of artificial intelligence technologies, in particular - the method of systemic cognitive analysis