Scientific Journal of KubSAU

Polythematic online scientific journal
of Kuban State Agrarian University
ISSN 1990-4665
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Name

Orlov Alexander Ivanovich

Scholastic degree




Academic rank

professor

Honorary rank

Organization, job position

Bauman Moscow State Technical University
   

Web site url

Email

prof-orlov@mail.ru


Articles count: 155

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229 kb

SOME PROBLEMS OF SOCIALECOLOGICAL MANAGEMENT IN MODERN ECONOMY

abstract 1051501004 issue 105 pp. 67 – 93 30.01.2015 ru 839
Classical economic textbooks assume that the effect of a particular company on the environment is infinitely small, in particular, that resources required for an industrial firm are available, and it's only the price to be paid for their involvement. For a large corporation, the situation is quite different. It converts the environment by means of its activity. Objectively existing resource limits are become important. The effects are increased when we consider the economy as a whole thing. Therefore, we have the obvious need for careful consideration of management problems in the real process of interaction between the economy, society and environment. This article is devoted to some approaches to this consideration. We have demonstrated that the economy is the servant of society. In all the economical developed countries in the twentieth century the role of the state in the economy has been increased in 3-5 times. We have discussed the influence of the modern ecological situation on the economy and management. In particular, we predict the end of private enterprise in the classical meaning. We examined the social-ecological aspects of management of the state and personnel of the firm. Discussion of Russian problems we begin with an analysis of the dynamics of the main economic and demographic indicators of Russia, including the total fertility rate in Russia. The system of scenarios of population projections for the period up to 2050 shows the inevitability of significant reduction in the Russian population (in the absence of intensive management actions). We describe two basic scenarios of solving socio-ecological conflicts
240 kb

STATE AND PROSPECTS OF APPLIED AND THEORETICAL STATISTICS

abstract 1151601013 issue 115 pp. 202 – 226 27.01.2016 ru 531
The general scheme of modern statistical science is just like this. Mathematical Statistics is a part of mathematics that studies the statistical structure (it itself does not give recipes analysis of statistical data, however, it is developing methods that are useful for use in theoretical statistics). Theoretical Statistics - the science dedicated to the models and methods of analysis of concrete statistical data. Applied Statistics (in the narrow sense) is devoted to the statistical techniques of data collection and processing (it includes the methodology of statistical methods, the organization of sample surveys, the development of statistical techniques, the creation and use of statistical software). Applications of statistical methods in concrete fields (in economics and management - Econometrics, in biology - Biometrics, in chemistry - Chemometrics, in technical research - Technometric, in geology, demography, sociology, medicine, history, etc.). Often positions 2 and 3 together are called Applied Statistics. Sometimes position 1 is called Theoretical Statistics. These terminological differences are related to the fact that the above-described development of the considered scientific and applied field not once, not completely and not always adequately reflected in the minds of experts. Meanwhile, there are still textbooks of appropriate level of representation of the mid-twentieth century. The article analyzes the post-war development of the national statistics. We have identified five "growth points": nonparametrics, robustness, bootstrap, statistics of interval data, and statistics of non-numeric data. We have discussed content, development and the basic ideas of statistics of nonnumeric data. We have given a number of unresolved problems of theoretical and applied statistics
215 kb

STATISTICAL ESTIMATION FOR THE GROUPED DATA

abstract 0981404080 issue 98 pp. 1113 – 1133 30.04.2014 ru 1052
The probabilistic model of grouping data (including multidimensional data) is described. We have also generalized Euler-Maclaurin’s formulas. With its help Sheppard’s corrections and corrections on grouping for correlation coefficient are received. We have found and studied asymptotical corrections on grouping data generally. Accuracy of approach has been estimated
229 kb

STATISTICAL HYPOTHESIS TESTING OF HOMOGENEITY OF MATHEMATICAL EXPECTATIONS OF TWO INDEPENDENT SAMPLES: CRAMER-WELCH TEST INSTEAD OF t-TEST

abstract 1101506013 issue 110 pp. 198 – 219 30.06.2015 ru 1476
Currently, the majority of scientific, technical and economic studies use statistical methods developed mainly in the first third of the XX century. They constitute the content of common textbooks. However, mathematical statistics are rapidly developing in the next 60 years. In some situations there is a need of the transition from classical to modern methods. As an example, we discuss the problem of testing the homogeneity of two independent samples. We have considered the conditions of applicability of the traditional method of testing the homogeneity based on the use of Student's t-statistic, as well as more up-to-date methods. We describe a probabilistic model of generation of statistical data in the problem of testing the homogeneity of two independent samples. In terms of this model the concept of "homogeneity" ("no difference"), can be formalized in different ways. High degree of homogeneity is achieved if the two samples are taken from one and the same population (absolute homogeneity). In some cases it is advisable to testing the coincidence of some characteristics of the elements of the sample - mathematical expectations, medians, variances, coefficients of variation, and others (testing the homogeneity of characteristics). To test the homogeneity of mathematical expectations is often recommended classic t-test. It is believed that the samples taken from a normal distributions with equal variances. It is shown that for scientific, technical and economic data the preconditions of two-sample t-test usually are not performed. To test the homogeneity of mathematical expectations instead of t-test we have offered to use the Cramer-Welch test. We have considered the consistent nonparametric Smirnov and Lehmann-Rosenblatt tests for absolute homogeneity
319 kb

STATISTICAL METHODS IN HISTORY

abstract 1151601014 issue 115 pp. 227 – 262 27.01.2016 ru 536
We have given a critical analysis of statistical models and methods for processing text information in historical records to establish the times when there were certain events, ie, to build science-based chronology. There are three main kinds of sources of knowledge of ancient history: ancient texts, the remains of material culture and traditions. The specific date of the extracted by archaeologists objects in most cases can not be found. The group of Academician A.T. Fomenko has developed and applied new statistical methods for analysis of historical texts (Chronicle), based on the intensive use of computer technology. Two major scientific results were: the majority of historical records that we know now, are duplicated (in particular, chronicles, describing the so-called "Ancient Rome" and "Middle Ages", talking about the same events); the known historical chronicles tell us about real events, separated from the present time for not more than 1000 years. It was found that chronicles describing the history of "ancient times" and "Middle Ages" and the chronicle of Chinese history and the history of various European countries do not talk about different, but about the same events. We have the attempt of a new dating of historical events and restoring the true history of human society based on new data. From the standpoint of statistical methods of historical records and images of their fragments – they are special cases of non-numeric objects of nature. Therefore, developed by the group of A.T. Fomenko computer-statistical methods are the part of non-numerical statistics. We have considered some methods of statistical analysis of chronicles applied by the group of A.T. Fomenko: correlation method of maximums; dynasties method; the method of attenuation frequency; questionnaire method codes. New chronology allows us to understand much of the battle of ideas in modern science and mass consciousness. It becomes clear the root cause of cautious attitude of the West towards Russia
266 kb

STATISTICAL MODELS IN MEDICINE

abstract 1241610063 issue 124 pp. 954 – 983 30.12.2016 ru 792
The article is devoted to the discussion of the organization of clinical-statistical studies and experiments. We have considered the examples of the application of statistical methods in scientific medical research. Under the clinical-statistical research we understand specially organized collection and analysis of medical data about the course of disease in patients, research of the dynamics of objective and subjective indicators of the state of reaction to these or other therapeutic effects. We study one, two or more groups of individuals (patients or healthy), conclusions are drawn on the whole group, but not for each individual patient. The purpose of research - to transfer the conclusions reached for the sample to the general population, i.e., clinical and statistical study focused on the production of useful recommendations concerning those patients who fall into the field of view of doctors after the end of the study. There are two main types of research - prospective and retrospective. The first related to the analysis of the last patients, the second - to monitoring the course of their disease in the future. We have considered typical mistakes in the organization of clinical-statistical studies. When planning a research, we usually distinguish the experimental and control groups, which are identical or similar in all respects except for the studied factors (exposure). We discuss the various options for blind methods and consider the application of statistical models and methods in scientific medical research. We have analyzed examples of confidence estimation of proportion (probability) and the homogeneity test of probabilities. For statistical modeling we use the Poisson distribution in the case of small probability. With its help, we analyze statistical data on the opisthorchiasis
185 kb

STATISTICS OF FUZZY DATA

abstract 1191605004 issue 119 pp. 75 – 91 31.05.2016 ru 674
Fuzzy sets are the special form of objects of nonnumeric nature. Therefore, in the processing of the sample, the elements of which are fuzzy sets, a variety of methods for the analysis of statistical data of any nature can be used - the calculation of the average, non-parametric density estimators, construction of diagnostic rules, etc. We have told about the development of our work on the theory of fuzziness (1975 - 2015). In the first of our work on fuzzy sets (1975), the theory of random sets is regarded as a generalization of the theory of fuzzy sets. In non-fiction series "Mathematics. Cybernetics" (publishing house "Knowledge") in 1980 the first book by a Soviet author fuzzy sets is published - our brochure "Optimization problems and fuzzy variables". This book is essentially a "squeeze" our research of 70-ies, ie, the research on the theory of stability and in particular on the statistics of objects of non-numeric nature, with a bias in the methodology. The book includes the main results of the fuzzy theory and its note to the random set theory, as well as new results (first publication!) of statistics of fuzzy sets. On the basis of further experience, you can expect that the theory of fuzzy sets will be more actively applied in organizational and economic modeling of industry management processes. We discuss the concept of the average value of a fuzzy set. We have considered a number of statements of problems of testing statistical hypotheses on fuzzy sets. We have also proposed and justified some algorithms for restore relationships between fuzzy variables; we have given the representation of various variants of fuzzy cluster analysis of data and variables and described some methods of collection and description of fuzzy data
1123 kb

SYSTEM FUZZY INTERVAL MATHEMATICS - A PROMISING AREA OF THEORETICAL AND COMPUTATIONAL MATHEMATICS

abstract 0911307015 issue 91 pp. 258 – 310 30.09.2013 ru 1551
The article b riefly considers the prospects of some “points of growth” in the modern theoretical and computational mathematics: the numbers and sets, i.e. the base of modern mathematics; mathematical, pragmatic and computer numbers; from the usual sets - to unclear; the theory of fuzzy sets and “fuzzy dou-bling” of mathematics; the mix of fuzzy set theory to the theory of random sets; interval numbers as a spe-cial case of fuzzy sets; development of interval mathematics (interval doubling of mathematics); the system as a generalization of a multitude; the systematic generalization of mathematics and tasks emerging; the systematic generalization of operations on sets (on the example of the operation of the Boolean association); the systematic generalization of the concept of functions and functional dependencies participation; cognitive function; the matrix of knowledge as fuzziness with an estimated degree of truth of showing data systems arguments on the system of values of the function; modification of the method of least squares for the approximation of cognitive functions; development of the idea of the systematic generalization of mathematics in the field of information theory – system emergent information theory; information measures of the level of consistency; ratios of emergence; direct and opposite, direct and indirect logical reasoning with an estimated level of truth; intellectual system of Eidos X++ as a toolkit that implements the ideas of system of a fuzzy interval sum of mathematics
263 kb

SYSTEM OF MODELS AND METHODS OF TESTING THE HOMOGENEITY OF TWO INDEPENDENT SAMPLES

abstract 1572003012 issue 157 pp. 145 – 169 31.03.2020 ru 178
The new paradigm of mathematical research methods allows us to give a systematic analysis of various statements of statistical analysis problems and methods for solving them, based on a probabilistic-statistical model of generating data accepted by the researcher. Methods for testing the homogeneity of two independent samples - a classic area of mathematical statistics. For more than 110 years since the publication of the fundamental Student’s article, various criteria have been developed for testing the statistical hypothesis of homogeneity in various statements, and their properties have been studied. However, the need for streamlining the totality of the scientific results found is urgent. It is necessary to analyze the whole variety of problem statements for testing the statistical hypotheses of the homogeneity of two independent samples, as well as the corresponding statistical criteria. This analysis is devoted to this article. It contains a summary of the main results concerning the methods for testing the homogeneity of two independent samples, and a comparative study of them, allowing the system to analyze the diversity of such methods in order to select the most appropriate for processing specific data. Based on the basic probabilistic-statistical model, the main statements of the problem of testing the homogeneity of two independent samples are formulated. A comparative analysis of the Student and Cramer - Welch criteria, designed to test the homogeneity of mathematical expectations, is given, a recommendation on the widespread use of the Cramer - Welch criterion is substantiated. From nonparametric methods for testing homogeneity, the criteria of Wilcoxon, Smirnov, Lehmann - Rosenblatt are considered. Dismantled two myths about the Wilcoxon criteria. Based on the analysis of the publications of the founders, the incorrectness of the term "Kolmogorov – Smirnov criterion" is shown. To verify absolute homogeneity, i.e. coincidence of the distribution functions of samples, it is recommended to use the Lehmann - Rosenblatt criterion. The current problems of the development and application of nonparametric criteria are discussed, including the difference between nominal and real significance levels, making it difficult to compare power of criteria, and the need to take into account coincidences of sample values (from the point of view of the classical theory of mathematical statistics, the probability of coincidences is 0)
285 kb

SYSTEM PARADIGM AS THE BASIS OF CREATION OF AGRO-INDUSTRIAL COMPLEX CONTROLLING SERVICE

abstract 1321708043 issue 132 pp. 518 – 548 31.10.2017 ru 255
System paradigm is discussed conformably to functioning of controlling institution of a large-scale agro-industrial system. Presently the systemacity became the general platform of fundamental and applied, scientific and practical elaborations and projects. Now in the sphere of system researches surge of interest in questions of classification is observed. Apparently, it is connected with accumulation of results of private researches in all areas of this discipline and with inevitable transdisciplinary crossings of their practical applications. So, undoubted intervention of high technologies to the agrarian sphere is observed. The efficiency of this introduction, certainly, depends on coordination of actions of developers of various subject domains. On the basis of the objective analysis it must be noted that in the arsenal of managers, especially foreign ones, there is practically no fundamentally new methods and tools of controlling. So says the executive director of Russian Association of Controllers prof. S. G. Falco. However, promising mathematical and instrumental methods of controlling actively developed in our country. It is necessary to implement them. For example, managers should be used advanced mathematical and instrumental methods of controlling. These methods are based on the modern development of mathematics as a whole - on the system interval fuzzy math. Considered methods are developed in accordance with the new paradigm of mathematical methods of research. It includes new paradigms of applied statistics, mathematical statistics, mathematical methods of economics, methods of analysis of statistical and expert data in management and control. In the XXI century there were more than 10 books issued, developed in accordance with the new paradigm of mathematical methods of research. The systems approach to solving specific applications often requires going beyond the economy. Very important are the procedures for the introduction of innovative methods and tools. In this article we consider the above research results in their interconnection
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