Scientific Journal of KubSAU

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

The work discusses various examples of physical systems which state is determined by the logarithmic law - quantum and classical statistical systems and relativistic motion in multidimensional spaces. It was established that the Fermi-Dirac statistics and BoseEinstein-Maxwell-Boltzmann distribution could be described by a single equation, which follows from Einstein's equations for systems with central symmetry. We have built the rate of emergence of classical and quantum systems. The interrelation between statistical and dynamic parameters in supergravity theory in spaces of arbitrary dimension was established. It is shown that the description of the motion of a large number of particles can be reduced to the problem of motion on a hypersphere. Radial motion in this model is reduced to the known distributions of quantum and classical statistics. The model of angular movement is reduced to a system of nonlinear equations describing the interaction of a test particle with sources logarithmic type. The HamiltonJacobi equation was integrated under the most general assumptions in the case of centrally-symmetric metric. The dependence of actions on the system parameters and metrics was found out. It is shown that in the case of fermions the action reaches extremum in fourdimensional space. In the case of bosons there is a local extremum of action in spaces of any dimension

In article the main problem of management of agro industrial holding is formulated and the basic results of its solution on the basis of application of the modern automated technology of management by knowledge, i.e. systemic-cognitive analysis (SC-analysis) are shown. The technology of cognitive functions of SC-analysis, providing both revealing of knowledge from empirical data, and use of this knowledge for decision-making support of management of holding as a whole, on the basis of management of characteristics of the sub-enterprises, is examined in details

The article briefly describes the essence of management, stating the goals and structure of the system of personnel management. It considers the essence of the method of functional-cost analysis (FCA) and, as a major gap, we have noted a low level of formalization, which requires the involvement of experts in applying the FSA. It also specifies the difference between the cost and the cost price. We consider the decision of questions of creation of the personnel management system on the FCA basis using the method of automated system-cognitive analysis (ASA-analysis), in particular: the measurement of the severity of socio-economic and psychological properties, metric scales, build intellectual measuring system, the development and application of models, providing both building occupation graphs and their application to measure the degree of compliance of the Respondent with the requirements of professional positions and to the positions including the cost of employment of personnel and resources allocated for staff on posts. The proposed approach can be applied not only at the decision of tasks of human resource management with DAF method, but when you apply the FSA in a variety of subject areas, in particular - the method of direct-Costing

The researchers obtained data on the morphological, biochemical and trace element composition of the blood of bull-calves of Hereford breed of different sizes. In this regard, scientists and business executives have three natural questions: 1) whether it is possible to predict the size and thus the meat productivity of bulls using these blood indicators; what are the strength and direction of the influence of certain values of blood indicators on the size and weight of bulls; what blood indicators are similar in meaning, and what are different and how much (to what extent). The article is devoted to the reasoned answers to these questions by applying modern methods of mathematical and numerical modeling to solve the corresponding problems. The results of the study can be used by anyone, due to the fact that Eidos the universal automated system, which is a tool of ask-analysis, is in full open free access on the author's website at: http://lc.kubagro.ru/aidos/_Aidos-X.htm, and numerical examples of solving the mentioned problems with the use of artificial intelligence technologies are placed as a cloud Eidos-application #133

The mathematical essence of systemic information theory(STI) offered by the author is the mathematic model of systemic-cognitive analysis ( SC-analysis) realized in its programming instruments – universal cognitive analytical system “AIDOS”.

In the article the mathematical model, a technique of numerical calculations (including algorithms and structures of data) and their program realization in an infrastructure of universal cognitive analytical system of "Eidos", and also the intellectual technology and a technique of revealing and research of functional dependences of volumes of production in regional agrarian and industrial complex from structure of expenses are offered. Results of appliance of the given intellectual technology on materials of agrarian and industrial complex of Krasnodar region are resulted and the recommendations about perfection of structure of expenses are offered on their basis

In this article, on a small and evident numerical example, methodological aspects of a process engineering of detection of knowledge from the trial-and-error data explicitly are considered, representation of knowledge and its usage for problem solving of forecasting, decision making and data domain examination in system-cognitive analysis (SC-analysis) and its programmatic toolkit - intellectual "Eidos" system are shown

In this article, on a small and evident numerical example, methodological aspects of a process engineering of detection of knowledge from the trial-and-error data explicitly are considered, representation of knowledge and its usage for problem solving of forecasting, decision making and data domain examination in system-cognitive analysis (SC-analysis) and its programmatic toolkit - intellectual "Eidos" system are shown

One of the "points of growth" of applied statistics is methods of reducing the dimension of statistical data. They are increasingly used in the analysis of data in specific applied research, such as sociology. We investigate the most promising methods to reduce the dimensionality. The principal components are one of the most commonly used methods to reduce the dimensionality. For visual analysis of data are often used the projections of original vectors on the plane of the first two principal components. Usually the data structure is clearly visible, highlighted compact clusters of objects and separately allocated vectors. The principal components are one method of factor analysis. The new idea of factor analysis in comparison with the method of principal components is that, based on loads, the factors breaks up into groups. In one group of factors, new factor is combined with a similar impact on the elements of the new basis. Then each group is recommended to leave one representative. Sometimes, instead of the choice of representative by calculation, a new factor that is central to the group in question. Reduced dimension occurs during the transition to the system factors, which are representatives of groups. Other factors are discarded. On the use of distance (proximity measures, indicators of differences) between features and extensive class are based methods of multidimensional scaling. The basic idea of this class of methods is to present each object as point of the geometric space (usually of dimension 1, 2, or 3) whose coordinates are the values of the hidden (latent) factors which combine to adequately describe the object. As an example of the application of probabilistic and statistical modeling and the results of statistics of non-numeric data, we justify the consistency of estimators of the dimension of the data in multidimensional scaling, which are proposed previously by Kruskal from heuristic considerations. We have considered a number of consistent estimations of dimension of models (in regression analysis and in theory of classification). We also give some information about the algorithms for reduce the dimensionality in the automated system-cognitive analysis