Scientific Journal of KubSAU

Polythematic online scientific journal
of Kuban State Agrarian University
ISSN 1990-4665
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Name

Lutsenko Yevgeniy Veniaminovich

Scholastic degree


Academic rank

professor

Honorary rank

Organization, job position

Kuban State Agrarian University
   

Web site url

lc.kubagro.ru

Email

prof.lutsenko@gmail.com


Articles count: 276

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862 kb

SYSTEM-COGNITIVE MODEL OF FORECASTING THE DEVELOPMENT OF DIVERSIFIED AGRO-INDUSTRIAL CORPORATIONS. PART II. SYNTHESIS AND MODEL VERIFICATION

abstract 1131509098 issue 113 pp. 1397 – 1410 30.11.2015 ru 856
In this article, in accordance with the methodology of the Automated system-cognitive analysis (ASCanalysis), we examine the implementation of the 3rd ASC-analysis: synthesis and verification of forecasting models of development of diversified agro-industrial corporations. In this step, we have synthesis and verification of 3 statistical and 7 system-cognitive models: ABS – matrix of the absolute frequencies, PRC1 and PRC2 – matrix of the conditional and unconditional distributions, INF1 and INF2 private criterion: the amount of knowledge based on A. Kharkevich, INF3 – private criterion: the Chi-square test: difference between the actual and the theoretically expected absolute frequencies INF4 and INF5 – private criterion: ROI - Return On Investment, INF6 and INF7 – private criterion: the difference between conditional and unconditional probability (coefficient of relationship). The reliability of the created models was assessed in accordance with the proposed metric is similar to the known F-test, but does not involve the performance of normal distribution, linearity of the object modeling, the independence and additivity acting factors. The accuracy of the obtained models was high enough to resolve the subsequent problems of identification, forecasting and decision making, as well as studies of the modeled object by studying its model, scheduled for consideration in future articles
665 kb

SYSTEM-COGNITIVE MODEL OF FORECASTING THE DEVELOPMENT OF DIVERSIFIED AGRO-INDUSTRIAL CORPORATIONS. PART I. COGNITIVE STRUCTURING AND FORMALIZATION OF THE SUBJECT AREA

abstract 1131509097 issue 113 pp. 1380 – 1396 30.11.2015 ru 1224
In this article, in accordance with the methodology of the Automated system-cognitive analysis (ASCanalysis), we examine the implementation of the 1st and 2nd stages of ASC-analysis: cognitive structuring and formalization of the subject area. At the stage of cognitive structurization of subject area, researchers decide what to consider as the object of modeling, the factors affecting it and the results of their actions. In accordance with the results of the cognitive structurization, we prepare the initial database for the study (training sample or case-based reasoning). At the stage of formalization of the subject area, the base of the original data is being normalized, i.e., we develop classification and description: the scale and graduations and with their use the base of the source data is being encoded. The result is a database of events (eventological database) and the training sample. The stage of cognitive structuring and preparation of the source data is not formalized and the formalization of the subject area is fully automated and performed directly with the use of the universal cognitive analytical system named "Eidos", which is a software Toolkit for ASC-analysis. Stages of cognitive structurization and formalization of the subject area of ASC-analysis are the first steps of data conversion into information and into knowledge. Subsequent steps: the synthesis and verification of system-cognitive model, the decision of problems of identification, forecasting and decision making, as well as studies of the modeled object by studying its model will be considered in future articles
2244 kb

SYSTEM-COGNITIVE ASPECTS OF AUTOMATION OF INVESTMENT CONTROL OF REGIONAL AGRIBUSINESS INDUSTRY WITH APPLICATION OF INTELLECTUAL PROCESS ENGINEERING

abstract 0721108045 issue 72 pp. 520 – 534 30.10.2011 ru 1104
In the article, the problem of agribusiness industry control is stated, the purposes of control and measure of its success, and also composition of the computerised management system, including control object, controlling system, informational-measuring system and also a subsystem of rendering of corrective actions are considered. What is offered: 1) the control purpose is to consider a raise of quality level of life of the population of region; 2) the capacity of measure of success of control is to consider indexes of quality level of life of the population; 3) numbers and direction of investments can be used as the controlling factor; 4) synthesis and verification of model of agrarian and industrial complex can be performed directly in a cycle of control, based on application of system-cognitive analisys (SC-analisis) and its programmatic tooling - "Eidos" intellectual system; 5) forecasting of evolution of agrarian and industrial complex and production of controlling solutions can be performed on the basis of cognitive model of agrarian and industrial complex with SC-analisis and application of "Eidos" system
284 kb

SYSTEM-COGNITIVE ANALYSIS OF EDUCATIONAL INFORMATION IN AN AGRICULTURAL UNIVERSITY AS A FACTOR IN QUALITY MANAGEMENT TRAINING FOR A REGIONAL AGRICULTURE COMPLEX

abstract 1291705001 issue 129 pp. 1 – 22 31.05.2017 ru 477
The rapidly developing processes in global information development of our society have had a significant impact on education. Recently, in agricultural and other universities the amount of generated and processed pedagogical information has dramatically increased. Spontaneously and purposefully, electronic databases of educational information and educational portals have been created. All these works require a significant investment of time and effort of the teaching staff (PPP) of higher education institutions and a large number of technical experts in the field of information technology; they also require appropriate computer and communications equipment. All this is already an accomplished fact. On the other hand, the question arises about the degree of meaningfulness and expediency of certain aspects of this process in the form in which it is actually carried out, and evaluation of its impact on the mission of the University in General: "Training high-quality professionals", in particular for the regional agro-industrial complex (AIC). Apparently, now this process develops spontaneously, and no one has planned it, considering on the one hand, the costs of various kinds on its implementation and on the other hand - ensuring its effectiveness in achieving the objectives and getting the intended desired results both in physical and valuable forms. The meaning and justification of this process can give only a substantial positive impact on improving the quality of education, and only when it has adequate and reasonable cost. For a reasoned response to these questions, the authors propose to apply the theory of reflexive management active objects, automated system-cognitive analysis (ASC-analysis), functional cost analysis (FCA) and the method of "Direct costing". A foundation for solving the problem: this is a great experience in teaching and research activities, a successful experience of the application of ASC-analysis and the FSA for personnel management; a software tool of ASC-analysis which is an intellectual system called "Eidos" (full open free access)
1123 kb

SYSTEM FUZZY INTERVAL MATHEMATICS - A PROMISING AREA OF THEORETICAL AND COMPUTATIONAL MATHEMATICS

abstract 0911307015 issue 91 pp. 258 – 310 30.09.2013 ru 1565
The 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
562 kb

SYNTHESIS, VERIFICATION, AND THE STABILITY RESEARCH OF THE SYSTEM-COGNITIVE MODEL OF PROCESSING COMPLEX REGION

abstract 1011407016 issue 101 pp. 305 – 333 30.09.2014 ru 1188
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
716 kb

SYNTHESIS OF THE SYSTEM-COGNITIVE MODELS OF A NATURAL-ECONOMIC SYSTEM, ITS USE FOR FORECASTING AND MANAGEMENT IN GRAIN PRODUCTION (Part 3 – forecasting and decision-making)

abstract 0901306059 issue 90 pp. 865 – 874 30.06.2013 ru 1691
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
363 kb

SYNTHESIS OF SYSTEMIC COGNITIVE MODEL OF NATURAL ECONOMIC SYSTEM AND ITS USE FOR PREDICTION AND CONTROL IN GRAIN PRODUCTION (Part 2 – transformation of empirical data into information)

abstract 0891305090 issue 89 pp. 1301 – 1319 29.05.2013 ru 1586
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
177 kb

SYNTHESIS OF SYSTEMIC COGNITIVE MODEL OF NATURAL ECONOMIC SYSTEM AND ITS USE FOR PREDICTION AND CONTROL IN GRAIN PRODUCTION (Part 1 - statement of the problem)

abstract 0891305089 issue 89 pp. 1288 – 1300 29.05.2013 ru 1699
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
1054 kb

SYNTHESIS OF SYSTEM-COGNOTIVE MODELS OF A NATURAL-ECONOMIC SYSTEM, ITS USE FOR FORECASTING AND MANAGEMENT IN GRAIN PRODUCTION (4 part - the research of the object of simulation through the study of its model)

abstract 0901306060 issue 90 pp. 875 – 895 30.06.2013 ru 1413
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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