#### Name

Lutsenko Yevgeniy Veniaminovich

#### Scholastic degree

•

#### Academic rank

professor

#### Honorary rank

â€”

#### Organization, job position

Kuban State Agrarian University

#### Web site url

## Articles count: 276

A determination system of the population health is a big complex hierarchical system. The current level of management of such systems involves the use of mathematical models and corresponding software tools for the accumulation of baseline data (monitoring), identification, prediction and decision-making. However, when modeling such large complex systems, we face a number of problems. The main problem is that in one model it is necessary to process a very large number of factors in a proper and comparable way, that are measured in different units, and different types of scales (numeric and text). Traditionally, to solve this problem and determine the values of individual criteria we use expert evaluation and desirability functions, and the integral criterion is the geometric mean. However, the traditional approach, currently applied in this field, has several disadvantages. First, in the traditional model it is defined in an expert way, which factors influence the decision of different problems in a positive way, which ones are negative and which ones do not affect. Second, for the numerical evaluation of influence factors on the solution of the problem we use different algorithms for calculating values of the desirability function for positively and negatively influencing factors which, when used as an integral criterion of the geometric average, leads to comparable results. Third, the use of normalized utility functions leads to the leveling force of the impact factors resulting in weak impact and the influencing factors are given the same variation in numeric values and have similar influence on integral criteria. All of the mentioned problems of the traditional approach have been resolved using Automated system-cognitive analysis (ASC-analysis) and its programmatic Toolkit â€“ Universal cognitive analytical system called "Eidos". In the proposed systemic cognitive model, for the values of environmental and economic factors, without the participation of the experts, we have calculated the amount and the sign of the information contained there about some values of indicators of population health

In complex multiparameter technical systems there are
numerous and varied physical processes which, on the
one hand, have a significant impact on the
performance of those systems, and on the other hand, it
is extremely difficult amenable to description in the
form of meaningful analytical models based on
equations, because these models must take into
account the specific features of the systems. As a
consequence, the development of conceptual analytical
models is a "hand-made work" and it is associated with
a large number of simplifying assumptions that reduce
their versatility and reliability. But there is also another
principle of modeling: the construction of
phenomenological information models, i.e. models that
do not have analytical forms of representation that
describes the simulated system superficially as a
"black box". Such models can be built directly based
on empirical data and with the appropriate software it
can be a standard technology much faster and much
less time consuming than developing meaningful
analytical models. On the other hand, the
phenomenological information model can be sufficient
to determine the rational design features and
parameters of the modes of operation of complex
technical systems. Besides, such phenomenological
models can be viewed as the first stage in the
development of meaningful analytical models. It is
proposed to use a new universal innovative method of
artificial intelligence for creating phenomenological
models of complex technical systems: automated
system-cognitive analysis (ASC-analysis) and its
programmatic Toolkit which is a 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 an Excel file. The system of
"Eidos" can directly (based on empirical
(experimental) data) calculate how much information about the results of the technical systems is contained
in the facts of possessing certain specific structural
elements and certain values of the parameters modes
of its work. On this basis, the system provides
research-based and appropriate recommendations for
the rational choice of design features and parameters
of the operation modes of the simulated system

It is well known that genetics studies the mechanisms of variation/heredity and widely uses the concept of "genetic information". While genetics considers the information as the content of the genetic code - structure of DNA and RNA included in the cell of a living organism. Genetics examines the mechanisms of recording, copying, readout of genetic information, the possibility of its modification and its influence on the characteristics and properties of the organism. In conversational and scientific language we know phrases, such as "Genes contain information about the characteristics/properties of the body." Paradoxically, we see no attempts to determine the amount of information contained in specific genes on specific characteristics or phenotypic properties of the organism. It would seem that the application of information theory in genetics is a completely natural and suggests itself. More strange that there are practically no works devoted to the application of information theory for solving problems of genetics. This article is intended, to some extent, to fill this gap on the example of calculating the amount of information in the genes of the characteristics or properties of different grape varieties. It examines the application of automated system-cognitive analysis (ASC-analysis), its mathematical model â€“ system of information theory and software tools â€“ intellectual system called "Eidos" for solving one of the important tasks of genetics: determine the amount of information contained in the genes on various phenotypic characteristics/properties of the grapes. To solve this problem, we perform the following steps: 1) cognitive-targeted structuring of the subject area; 2) the formalization of the subject area, i.e. development of classification and descriptive dials and graduations and training samples; 3) synthesis and verification of information model, reflecting the amount of information in the genes on the phenotypic characteristics/properties (multiparameter typing); 4) displaying the information about the genetic determination system of phenotypic characteristics/properties (SWOT analysis of Fennovoima); 5) displaying the information about the strength and direction of influence of a specific gene on phenotypic characteristics/properties (SWOT-diagrams of genes); 6) the solution to the problem of system identification phenotypic characteristics/properties by the presence of certain genes; 7) quantification of the similarities-differences of the various phenotypic characteristics/properties, upon determination system genes. A specific phenotypic property (or characteristic) is regarded as a noisy genetic text, including genetic information about the true gene property (clean signal) and the noise that distorts this information due to the random effects of the environment. The software tool of the ask-analysis which is "Eidos" intellectual system provides the noise suppression and the selection of true signal

From a huge number of the organisms inhabiting our
planet, insects make 70%, being the most numerous of
the invertebrate animal classes numbering more than 2
million types. It is difficult to find such place where it
would be impossible to meet representatives of this
huge class. They completely took over the entire environment
- water, the land, air. For them, it is the common
characteristic: complex instincts, omnivorous,
high fecundity, and for some of them â€“ a public way of
life. Insects can be found at tremendous heights, reaching
the level of 5000 meters, and they inhabit the desert
where it practically never rains, not to mention the
absence of any vegetation. Deep caves where no sunlight,
nor the conditions for food and existence of living
organisms â€” it is also the habitat of insects, they
can be found far beyond the Arctic circle, and even on
many Islands of Antarctica, where in addition to lifeless
rock, it would seem that there is nothing else.
Among insects, one of the largest and most numerous
families are the ground beetles (Carabidae). They subtly
respond to changes in soil and vegetation, hydrothermal
and micro-climatic conditions of the environment,
which makes them a convenient model subject
to various environmental and Zoological researches.
Ground beetles belong to a large number of genera and
species, often difficult to see, in this regard, we use
many different signs to diagnose. We have taken into
consideration the coloration, body shape, external
structure, surface structure, size, and arrangement of
the genitals and chaetotaxy. Due to the fact, that the
number of ground beetles is enormous, and, using their
appearance, it is very difficult to determine their generic
identity, there is a need of automation of the
identification process, due to which we require a special
mechanism that would increase the accuracy of
these insects. In the previous work of the authors (http://ej.kubagro.ru/2016/05/pdf/01.pdf) we considered
the further possibility of using the method of
ASC- analysis to classify insects, not only in species
but also in genera, orders, thereby increasing the reliability
of determination of ground beetles, which will
be done in this article. A numerical example is given.
We also have gained a successful experience of solving
such problems in other subject areas. This article
can be considered as a continuation of the series of
works dedicated to governmental use of the automated
system-cognitive analysis (ASC-analysis) and its software
tools â€“ the system of "Eidos"

Adequate and effective assessment of the efficiency, effectiveness and the quality of scientific activities of specific scientists and research teams is crucial for any information society and a 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 his 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. The world has 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 the information about citation of these publications from more than 6,000 Russian journals. There is too much information; it is so-called "Big data". But the problem is how to make sense of these large data, more precisely, to identify the meaning of scientometric indicators) and thus to convert them into great information ("great information"), and then apply this information to achieve the objective of scientometrics, i.e. to transform it into a lot of knowledge ("great knowledge") about the specific scientists and research teams. The solution to this problem is creating a "Scientific smart metering system" based on the use of the automated system-cognitive analysis and its software tools â€“ an intellectual system called "Eidos". The article provides a numerical example of the creation and application of Scientometric intelligent measurement system based on a small amount of real scientific data that are publicly available using free on-line access to the RSCI

To increase the validity of conclusions about the impact of environment on quality of life we need to move from generalities to the application of quantitative modeling techniques. This requires the joint processing environmental databases and databases depicting various aspects of quality of life. These databases need to be handled not just together, but in a comparable form approach, technology and methodology; and we need to implement them in one software system. For the first time in the environmental studies it has been planned to be done with the application of the ASK- analysis and the system called "Eidos". In this work, we set the goals and the objectives of the application of the ASK-analysis to study the effect of environmental factors on the quality of life of the population of the region. The article reveals the urgency of this study; the requirements for the method of conducting the study, the choice of research method, the contents of the objectives of the study. The proposed work is at the edge of mathematical ecology and mathematical modeling of quality of life (which refers to mathematical and instrumental methods of Economics), resulting from expected synergies, consists in obtaining of new knowledge in these fields, that is relevant to both ecology and economy. This knowledge will make it more meaningful and justified for the application of environmental criteria and concepts in the economy

To increase the validity of conclusions about the impact of the environment on the quality of life we need to move from generalities to the application of quantitative modeling techniques. This requires the joint processing environmental databases and databases depicting various aspects of quality of life. These databases are needed to be handled not just together, but in a comparable form approach, including technology and methodology, and to be implemented in one software system. For the first time in the environmental studies, it has been planned to be done with the application of the ASK-analysis and the system called "Eidos". Previously, the authors have set the goals and the objectives of the application of the ASK-analysis to study the effect of environmental factors on the quality of life of the population of the region. The article reveals the urgency of this study; the requirements for the method of conducting the study, the choice of a research method; as well as the contents of the objectives of the study. The proposed work is at the edge of mathematical ecology and mathematical modeling of quality of life (which refers to mathematical and instrumental methods of Economics), resulting from expected synergies, consists in obtaining of new knowledge in these fields that is relevant to both ecology and economy. This knowledge will make it more meaningful and justified for the application of environmental criteria and concepts in the economy. This work contains a description of the basic data sources for the study of the impact of environmental factors on various aspects of quality of life of the region's population, the source data for this study, the characteristics of the original data, substantiation of requirements to the method of research, choosing research methods appropriate to requirements; the development of steps to achieve the objectives of the study

The application of classical forecasting methods applied to a diversified corporation faces some certain difficulties, due to its economic nature. Unlike other businesses, diversified corporations are characterized by multidimensional arrays of data with a high degree of distortion and fragmentation of information due to the cumulative effect of the incompleteness and distortion of accounting information from the enterprises in it. Under these conditions, the applied methods and tools must have high resolution and work effectively with large databases with incomplete information, ensure the correct common comparable quantitative processing of the heterogeneous nature of the factors measured in different units. It is therefore necessary to select or develop some methods that can work with complex poorly formalized tasks. This fact substantiates the relevance of the problem of developing models, methods and tools for solving the problem of forecasting the development of diversified corporations. This is the subject of this work, which makes it relevant. The work aims to: 1) analyze the forecasting methods to justify the choice of system-cognitive analysis as one of the effective methods for the prediction of semi-structured tasks; 2) to adapt and develop the method of systemic-cognitive analysis for forecasting of dynamics of development of the corporation subject to the scenario approach; 3) to develop predictive model scenarios of changes in basic economic indicators of development of the corporation and to assess their credibility; 4) determine the analytical form of the dependence between past and future scenarios of various economic indicators; 5) develop analytical models weighing predictable scenarios, taking into account all prediction results with positive levels of similarity, to increase the level of reliability of forecasts; 6) to develop a calculation procedure to assess the strength of influence on the corporation (sensitivity) of its member enterprises; 7) to finalize the software tools the ask analysis to the level of information technology, given its adaptation and development to predict actions in a diversified corporation

Application of classical forecasting methods applied to a diversified corporation faces some certain difficulties, due to its economic nature. Unlike other businesses, diversified corporations are characterized by multidimensional arrays of data with a high degree of distortion and fragmentation of the information due to the cumulative effect of the incompleteness and distortion of accounting information from its enterprises. Under these conditions, the applied methods and tools must have high resolution and to work effectively with large databases with incomplete information, to ensure correct common comparable quantitative processing of the heterogeneous nature of the factors measured in different units. It is therefore necessary to select or develop some methods that can work with poorly formalized complex tasks. This fact substantiates the relevance of the problem of developing models, methods and tools for solving the problem of forecasting the development of diversified corporations. This article compares methods of forecasting and encourages using the ask analysis which has a good theoretical justification for the meaningful interpretation of a knowledge model based on information theory; high accuracy and independence of calculation results of the unit of measurement baseline data through the use of not the correlation matrix, as in statistical systems, and matrices of knowledge. A well-developed and available Toolkit of the ASK-analysis which is an intellectual system called "Eidos" (created by E. V. Lutsenko, 1994) allows, on the basis of fragmented, noisy source data of various nature (numeric, text) to create models of large dimension. The ASK-analysis and the system of "Eidos" have been widely and successfully used in economics, engineering, agriculture, sociology and other fields. These features of the ASK-analysis have led to the fact that it was chosen as the method of forecasting of dynamics of indicators of the corporation

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 authorsâ€™ 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