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: 266

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612 kb

METRIZATION OF MEASURING SCALES OF DIFFERENT TYPES AND JOINT COMPARABLE QUANTITATIVE PROCESSING OF HETEROGENEOUS FACTORS IN SYSTEM-COGNITIVE ANALYSIS AND THE EIDOS SYSTEM

abstract 0921308058 issue 92 pp. 860 – 884 31.10.2013 ru 1544
The article considers measuring scales as a tool for creating formal models of real objects and a tool for increasing the degree of formalization of these models to a level sufficient to implement them on computers. It also describes the different types of measuring scales, allowing to create models of varying degrees of formalization; lists the types of transformation valid during the processing of empirical data obtained with scales of different types; develops the task of metriza-tion of the scales, i.e. conversion to the most formalized mind; it proposes 7 ways of metrization of all the types of scales, providing a joint comparable quantitative processing of heterogeneous factors measured in different units of measure due to the conversion of all scales to one universal unit of measurement in which the measurement number of information is selected. All of these methods of metrization have been implemented in the system-cognitive analysis and in the Eidos intellectual system
1051 kb

MODELING COMPLEX MULTIFACTOR NONLINEAR CONTROL OBJECTS BASED ON A FRAGMENTED NOISY EMPIRICAL HIGH-DIMENSIONAL DATA IN A SYSTEM COGNITIVE ANALYSIS AND IN THE INTELLECTUAL EIDOS-X++ SYSTEM

abstract 0911307012 issue 91 pp. 167 – 191 30.09.2013 ru 1447
In the article, we have considered the application of a system-cognitive analysis and the Eidos-X++ intellec-tual system to create complex multifactor models of nonlinear control objects on the basis of noisy frag-mented empirical data of large dimension and for the use of these models to solve problems of forecasting, executive decision making and research of the model objects. We have formulated the systematic generalization of the principle of Ashby (for nonlinear systems). The numerical example of a study of an abstract nonlinear system (Lissajous figures), in which the combined effect of multiple factors is the sum of the influences of each of these factors separately, that says about non-compliance of these factors, the principle of superposition and nonlinear effects in the system under consideration. It is shown, that the proposed device and software tools allow us to model such systems. We note, that the proposed device and instrumentation allow to interpret some classification scale, as projected geographical coordinates of the event, and others, like the foreseeable events and their severity, which allows you to get cartographic visualization of recognition of the place and time of events
3166 kb

MODIFICATION OF THE METHOD OF WEIGHTED LEAST SQUARES BY USING THE OBSERVATIONS OF THE AMOUNT OF INFORMATION IN THE ARGUMENT OF THE VALUE FUNCTION AS WEIGHTS (ALGORITHM AND SOFTWARE IMPLEMENTATION)

abstract 1041410100 issue 104 pp. 1390 – 1440 30.12.2014 ru 728
The method of ordinary least squares (OLS) is widely known and deservedly popular. However, some attempts to improve this method. The result of one of such attempts is the weighted least squares (WMNC), the essence of which is to give the observation a weight which is inversely proportional to the errors of their approximation. Thereby, in fact, monitoring is ignored the more the difficult to approximate it. The result of this approach, formally, is the approximation error decreasing, but in fact, this occurs by partial refusal to consider the "problem" of observations, making a big mistake. If the idea underlying WMNC to bring to the extreme (and absurd), then in the limit, this approach will lead to the fact that from the entire set of observations there will be only those that lie almost exactly on the trend obtained by the method of least squares, and the rest will simply be ignored. However, according to the author, it's not a problem, and the failure of its decision, though it might look like a solution. In the work we have proposed a solution, based on the theory of information: to consider the weight of observations, the number of the argument of the value function. This approach was validated in the framework of a new innovative method of artificial intelligence: methods for automated system-cognitive analysis (ASA-analysis) and implemented 30 years ago in its software toolkit, which is "Eidos" intelligent system in the form of so-called "cognitive functions". This article presents an algorithm and software implementation of this approach, illustrated in detailed numerical example. In the future it is planned to give a detailed mathematical basis of the method of weighted least squares, which is modified by the application of information theory to calculate the weights of the observations, and investigate its properties
615 kb

MODIFICATION OF WEIGHTED LEAST SQUARES BY USING THE OBSERVATIONS OF THE AMOUNT OF INFORMATION IN THEM AS WEIGHTS (MATHEMATICAL ASPECTS)

abstract 1051501050 issue 105 pp. 813 – 844 30.01.2015 ru 732
This article briefly discusses the mathematical nature of the author's proposed modification of the weighted least squares, in which the amount of the data is used as the weights of observations. There are two variants of this modification. In the first one, the weighting of the observations was made by replacing one observation with a certain amount of the information in it by the corresponding number of observations for unit weight, and then we applied the standard method of least squares. In the second method, the weighting of the observations was performed for each value of the argument by replacing all observations with a certain amount of information in one observation of unit weight which had been obtained as a weighted average of them, and then we applied the standard method of least squares. We have described in detail the technique of numerical calculations of the amount of information in the observations, based on the theory of automated system-cognitive analysis (ASC-analysis) and implemented it with a help of software tools - intelligent system called "Eidos". The article provides an illustration of the proposed approach on a simple numerical example. In the future, we are planning to give more detailed mathematical basis of the method of weighted least squares, which is modified by using the amount of information as weights, but also to explore its properties
563 kb

ON-LINE FORECASTING OF THE TRENDS OF ECONOMICAL INDEXES OF DIVERSIFIED CORPORATION WITH APPLICATION OF PROCESS ENGINEERINGS OF ARTIFICIAL INTELLIGENCE (part 1: problem definition and data domain formalization)

abstract 0731109043 issue 73 pp. 471 – 483 30.11.2011 ru 1696
In this article, the problem of short-range forecasting of the trends of economical indexes of diversified corporation is stated, on the basis of application of systemic-cognitive analysis and its tooling (intellectual system "Eidos") the formal problem definition and data domain formalization, i.e. development of classification and descriptive dials and graduations and shaping of training sample is performed
465 kb

ON-LINE FORECASTING OF THE TRENDS OF ECONOMICAL INDEXES OF DIVERSIFIED CORPORATION WITH APPLICATION OF PROCESS ENGINEERINGS OF ARTIFICIAL INTELLIGENCE (part 2: synthesis and model verification)

abstract 0731109044 issue 73 pp. 484 – 493 30.11.2011 ru 1882
In this article, the routine of synthesis of four models of the corporation, different by frequent measure of correlation between past indexes of the factories entering into corporation and the future statuses of corporation as a whole is featured, verification of all private models with utilization of two integral measure is fabricated, forecasting of the future statuses of corporation on their system of determination is performed
798 kb

ON-LINE FORECASTING OF VALUE OF ECONOMICAL INDEXES OF DIVERSIFIED CORPORATION WITH APPLICATION OF PROCESS ENGINEERINGS OF ARTIFICIAL INTELLIGENCE (part 1: problem definition and data domain formalization)

abstract 0711107049 issue 71 pp. 696 – 709 30.09.2011 ru 1470
In this article, the problem of short-range forecasting of value and dynamics of economical indexes of diversified corporation is stated, on the basis of application of systemic-cognitive analysis and its tooling (intellectual system "Eidos") the formal problem definition and data domain formalization, i.e. development of classification and descriptive dials and graduations and shaping of training sample is performed
22698 kb

ON-LINE FORECASTING OF VALUE OF ECONOMICAL INDEXES OF DIVERSIFIED CORPORATION WITH APPLICATION OF PROCESS ENGINEERINGS OF ARTIFICIAL INTELLIGENCE (part 2: synthesis and model ve-rification)

abstract 0711107050 issue 71 pp. 710 – 723 30.09.2011 ru 1138
In this article, the routine of synthesis of four models of the corporation, different by frequent measure of correlation between past indexes of the factories entering into corporation and the future statuses of corporation as a whole is featured, verification of all private models with utilization of two integral measure is fabricated, forecasting of the future statuses of corporation on their system of determination is performed
511 kb

PREDICTION OF SEISMIC ACTIVITY AND CLIMATE ON THE BASIS OF SEMANTIC INFORMATION MODELING

abstract 0530909009 issue 53 pp. 98 – 122 30.11.2009 ru 2569
On the basis of semantic information models examined the dependence of parameters of seismic activity on the gravity of celestial bodies. The regional semantic information model of climate is developed
4259 kb

PREDICTION OF SURVIVAL IN PATIENTS WHO HAVE HAD A HEART ATTACK, ACCORDING TO ECHO-CARDIOGRAPHIC DATABASE OF UCI REPOSITORY

abstract 1021408082 issue 102 pp. 1274 – 1320 31.10.2014 ru 752
Since there are many artificial intelligence systems, there is a need of comparable quality assessment of their mathematical models. For this purpose, these systems can be tested on the same database source data, for which it is very convenient to use a public database of the UCI repository. This work is aimed at the study and development of model practices of the database of the UCI repository to assess the quality of mathematical models of artificial intelligence systems
.