Scientific Journal of KubSAU

Polythematic online scientific journal
of Kuban State Agrarian University
ISSN 1990-4665
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Poznysheva Natalya Olegovna

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Honorary rank

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Kuban State Agrarian University
   

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Articles count: 3

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360 kb

FORECASTING OF SUNFLOWER YIELD FOR THE KRASNODAR REGION WITH THE USE OF SYSTEM-COGNITIVE ANALYSIS (PART I: PROBLEMS OF STUDY)

abstract 0841210030 issue 84 pp. 359 – 375 28.12.2012 ru 1751
In this article the general form of the formulated prob-lem of the creation of the scientific-informed and ef-fective tool for forecasting dynamics of sunflower yield in the areas of the Krasnodar region and in the whole region. We have proposed and substantiated the possibility to predict scenario of sunflower yield through the application of artificial intelligence tech-nologies, in particular, of the method of system-cognitive analysis
448 kb

FORECASTING OF SUNFLOWER YIELD FOR THE KRASNODAR REGION WITH THE USE OF SYSTEM-COGNITIVE ANALYSIS (PART II: Formal statement of the problem and the transfor-mation of raw data into information, and infor-mation into knowledge)

abstract 0841210031 issue 84 pp. 376 – 401 28.12.2012 ru 1379
In this article, for the first time, the synthesis and veri-fication of the system-cognitive model of artificial ecosystems of sunflower crops in the Krasnodar region (at the levels of regions and in the whole region) are carried out. On the basis of the developed models, there are solved tasks: 1. Forecasting scenario of sun-flower yield for the period from 1 to 5 years. 2. The scientific study of artificial ecosystems of sunflower crops in the Krasnodar region (at the levels of regions and in the whole region)
1212 kb

FORECASTING OF SUNFLOWER YIELD FOR THE KRASNODAR REGION WITH THE USE OF SYSTEM-COGNITIVE ANALYSIS (PART III: Decision of the tasks of forecasting and research of the subject area)

abstract 0841210032 issue 84 pp. 402 – 427 28.12.2012 ru 1902
In the article we have offered the technology and the methodology for the formulation and the solution of the problem of forecasting scenarios of changes in yield sunflower seeds at the level of a region and its districts, on the basis of the system-cognitive model that is different from the traditional: a high degree of formalization of the model of knowledge; the possibil-ity of the synthesis matrix transfer function of the object of forecasting directly on the basis of empirical data; correct work with incomplete (fragmented) and noisy data. For the first time, the study of the system-cognitive model of artificial ecosystems of sunflower in the Krasnodar Region, which is correctly regarded as the study of the ecosystem, as the verification of this model has shown its high adequacy has been conduct-ed
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