Scientific Journal of KubSAU

The article presents results of the study to assess the effectiveness of credit funds in interacting agricultural (AES) and processing (PP) agricultural enterprises. The conducted studies are a continuation of the scientific work on the development of mathematical models of interaction of the enterprises of the AES and PP, are shown in the articles [1, 2, 3]. This article presents the authors’ developed set of models of management of credit funds of interacting enterprises of an agroindustrial complex. It includes mathematical models of economic efficiency of agricultural enterprises considering the use of loan funds, as well as the assessment of the maximum amount of interest rate of the loan and the minimum selling prices of units of finished agricultural products; a mathematical model of the economic efficiency of the processing plant taking into account credit obligations of the agricultural enterprise and a model for the calculation of the minimum selling prices of its finished products; a mathematical model of the economic efficiency of the combined entity with all its loans. We have proposed a model to calculate the minimum selling prices of its finished products

The quality of life of the population of the region is an important integral criterion of estimation of efficiency of activity of regional administration. The most important strategic sector of the economy of the Krasnodar region is the agro-industrial complex (AIC). This poses the problem of management of the quality of life of the region through the use of as the control factor of the volume and direction of investment in agriculture

The article is devoted to the solution of the problem which is the fact that on the one hand, the rating of Russian universities is in demand and on the other hand it hasn’t been created yet. The proposed idea of solving the problem consists in the application of domestic licensing of innovative intelligent technologies for these purposes: we have suggested using an automated system-cognitive analysis (ASC-analysis) and its software tools – the intelligent system called "Eidos". These methods are described in detail in this context. It is proposed to consider the possibility of applying these tools on the example of the Guardian University ranking. The article discusses its private criteria (indicators of universities). We specify the sources of data and the methods of their preparation for processing in "Eidos" system. In accordance with ASC-analysis methodology the article describes the installation of "Eidos", the data input into it, and the formalization of the subject area, synthesis and verification of models, their display and use to solve problems of assessment of the Guardian rating for Russian universities and research object modeling. It also discusses the prospects and ways of development of the integrated rating of Russian universities and operation of rating in adaptive mode. We have also specified the limitations of the proposed approach and the prospects of its development

Insects are a major component of natural biocenoses and agrocenoses. One of the largest and most numerous families are ground beetles (Carabidae); their number, according to various estimates, is more than 30,000 species. For Carabidae beetles it is common to have different ways of eating, a place of habitation, occupied layers, seasonal and daily activity. They live both on the surface and in the soil, more rarely on bushes and trees. The types of the family of ground beetles – active beetles with long, thin antennae of uniform thickness, long elytra and long legs, adapted to running. Their sizes vary from a few millimeters to 10 cm. As active predators, ground beetles play a huge practical importance, destroying pests before reaching the last threshold, thereby providing a natural regulation. Based on the fact, that the number of beetles is large, and their sizes are sometimes only a few millimeters, there is a problem of determining the species of these insects (or their identification), therefore it took a special tool, which, on the one hand, facilitate obtaining data about these insects, and on the other hand, would increase their accuracy. This article proposes a new (to this subject area) approach to identify different species of ground beetles along their outer contour with the use of software tools for automated system-cognitive analysis (ASC-analysis) – the universal cognitive analytical system called "Eidos," which is well-proven in the study of other objects. The reason why it was decided to use this system is that normal (standard) identification of ground beetles, have certain disadvantages: the human factor (manifest error in the determination); quite time consuming; the inability to increase the number of criteria to improve the reliability of the model comparison. This article aims to overcome these drawbacks, by the use of universal cognitive analytical system "Eidos", the automated system-cognitive analysis (ASC-analysis). A numerical example is given

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

A diversified corporation is a highly complex multivariable dynamic system. The application of classical forecasting methods applied to such objects has encountered a number of difficulties, due to its economic nature. In the article, we substantiate the requirements to the forecasting method; on the basis of these requirements we can select the method and its software tool

The performance indicators of a trading company in physical and monetary terms is significantly affected by the types and volumes of purchased and sold products, and which she purchased suppliers and the consumers sold. However, the solution to the problem of choosing the rational range of products faces considerable cost of computational and human resources, and lack of baseline data, and in real dimensions this problem has no solution. The paper proposes such a solution is very economical in costs of different types of resources based on the application of information theory, cognitive and control theory

Creation of artificial intelligence systems is one of important and perspective directions of development of modern information technology. As there are many alternatives to artificial intelligence systems, there is a need to evaluate mathematical models of these systems. In this work, we present a solution of the problem of identifying classes of salary levels of employees depending on their characteristics. To achieve this goal it requires free access to test the source data and methodology, which will help to convert the data into the form needed for work in artificial intelligence systems. A good choice is a database of test problems for systems of artificial intelligence of UCI repository. In this work we used the database called "Wine Data Set" from the Bank's original task of artificial intelligence from repository UCI. The most reliable in this application was the model of the INF4 based on semantic, according to A. Kharkevich, integral criteria of "Amount of knowledge". The accuracy of the model is 0,916, which is much higher than the reliability of expert evaluations, which is equal to about 70%. To assess the reliability of the models in the ASC-analysis and the system of "Eidos" we used the F-criterion of van Ritbergen and fuzzy multiCLASS generalization proposed by Professor E. V. Lutsenko (L-measure)

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"

The authors have developed and manufactured a large number of different designs of relative helical drums for mixing animal feed. We have conducted 749 field experiments with the drums of the 10 different designs with different parameters modes of operation. In all experiments, we measured the quality of the feed mixture. However, directly based on empirical data, rational choice of design features and parameters of the operation modes of the reels is not possible. For this, you must first develop a model reflecting these empirical data. The construction of meaningful analytical models of different types of drums is a difficult and demanding scientific task, the complexity of which is due to the large variety and complexity of forms of drums and their mode of usage, a large number of diverse physical factors affecting the processes in the drum. As a consequence, the development of analytical models associated with a large number of simplifying assumptions that reduce their versatility and reliability. Therefore, it is important to search of a mathematical method and software tools provide a quick and simple for the user to identify and influence the design of the drum and the parameters of the operating modes on the quality of the feed mixture directly on the basis of empirical (experimental) data. The work proposes a solution to this problem with the use of a new universal innovative method of artificial intelligence: automated system-cognitive analysis (ASC-analysis) and its programmatic Toolkit – universal cognitive analytical system called "Eidos". In the system of "Eidos" we have implemented a software interface that provides direct input into the system large amounts of empirical data from Excel file. Created on their basis in the system of "Eidos" system-cognitive model allows the visual form to reflect the effect of the structure of the drum and the parameters of the operating modes on the quality of the resulting feed mixture and to develop on this basis the science-based and appropriate recommendations for the rational choice of design features and parameters of the modes relative to the screw drums. We have also given a numerical example