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: 123

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279 kb

MAIN PROBLEMS OF CONTROLLING OF THE QUALITY

abstract 1111507004 issue 111 pp. 20 – 52 30.09.2015 ru 559
Controlling of statistical methods to ensure product quality is the special case of controlling organizational and economic methods of management. Today, controlling in the practice of management of Russian companies is understood as "the system of information-analytical and methodological support to achieve their goals." The controller is developing a decision-making rules, the head takes decisions on the basis of these rules. We proved the concept of "controlling of methods". Innovation in management is based, in particular, on the use of new adequate organizational-economic (as well as economicmathematical and statistical) methods. Controlling in this area - is the development and application procedures of compliance management used and newly developed (implemented) organizationaleconomic methods for the task. Thus, the methodology for controlling is of great practical value in any field in which the actions (operations) must be carried out in accordance with certain rules (regulations, standards, guidelines), as in any such area in which we need to use development and application procedures of compliance management used and the newly established (implemented) rules for solution of tasks assigned to the organization. In this article, we select a area of controlling as controlling quality, and we discuss its main issues. This is about controlling of organizational-economic methods to ensure product quality, especially about the statistical methods based on probability theory and mathematical statistics. We consider the analysis and synthesis of plans of statistical quality control, optimization options plans of statistical control, truncated plans. Are discussed the differences control plans provider and the consumer, the allocation of units formless (liquid, gas) products, the selection of a random sample of the statistical quality control of products, lower estimate of the required sample size. It is established, that is not always necessary quality control. Is given the theory of the basic paradox of statistical quality control. We discuss the development of statistical methods for quality control in our country. Is given the classification of statistical methods of quality management
715 kb

MANAGEMENT PROBLEMS IN SMALL PRODUCTION COMPANIES AT EARLY LIFECYCLE STAGES

abstract 1181604015 issue 118 pp. 275 – 304 29.04.2016 ru 170
In 1970 in the journal publications of "Forbes" and "Business week" the term of "startup" appeared, which later became popular in the scientific and business literature. Startups are the organizations, which create a new product or service under conditions of high uncertainty. In the last 25-30 years, due to Russia's transition from a planned economy to the mixed, many researchers and practitioners in the field of management, economics and entrepreneurship are concerned of some questions of small business, including production. It is particularly acute problem of deaths of Russian small businesses: only three out of a hundred small businesses manage to survive for more than 3 years. In addition, one of the main reasons, why we have such statistics, is management deficiencies and administrative errors, which are studied in this article. We are primarily interested in small manufacturing plants and problems of development in the early stages of the life cycle. In the literature, it has been given just little attention. A small production company is a company associated with the production organization or incorporation of the product / technology in the production process. We regard the small production companies at an early stage of development, working in the field of mechanical engineering, instrumentation, energy, telecommunications, robotics, materials production. In this work, we analyze the first foreign and then domestic research on small business, discuss the problems of management of small industrial enterprises in the early stages of the life cycle (based on the results of our questionnaire studies) and as an example, consider the story of a startup - All-Union Center of statistical methods and Informatics of Central Board of the All-Union economic society (now - Institute of high statistical technologies and econometrics of Bauman Moscow State Technical University)
282 kb

MATHEMATICAL METHODS IN SOCIOLOGY DURING THE LAST FORTYFIVE YEARS

abstract 1171603004 issue 117 pp. 93 – 121 31.03.2016 ru 546
Sociology is one of the most important social sciences. Mathematical and primarily statistical methods are effective intellectual tools of sociologists. Let us analyze the work of the author of this article on the development of statistical methods to meet the challenges of sociology. Then we give the review of development of statistical methods in Russian sociology for 45 years (1970-2015). The basic scientific events of these years, first of all, were formation of applied statistics and its basis - statistics of the non-numerical data (in sociology of 70-90% of variables have non-numerical nature). Over the last 30 years, the Russian sociology has been growing rapidly in all quantitative parameters. Clearly, the depth of investigation gives the use of advanced scientific apparatus - methodology and methods of data collection and analysis, mathematical models. In our view, a fundamental breakthrough was made in our country in the 1970s. It was then in the arsenal of Russian sociologists appeared measurement theory and fuzzy sets, mathematical methods of classification and multidimensional scaling, nonparametric statistics and statistics of non-numeric data. In subsequent decades it has been a natural development of scientific apparatus. The same mathematical and statistical methods and models can be successfully applied in various fields of science and practice. Statistical methods and models are very effective in sociological, socio-economic, managerial, technical and feasibility studies, medicine, history, in almost any industry and application areas of knowledge. Within this field, the main event of the last thirty five years - is becoming a scientific and practical discipline "Applied Statistics", dedicated to the development and application of statistical methods and models. An analysis of the dynamics of applied statistics leads to the conclusion that in the XXI century the statistics of non-numerical data is becoming a central area of applied statistics, as it contains the most common approaches and results
342 kb

MATHEMATICAL METHODS OF CLASSIFICATION THEORY

abstract 0951401023 issue 95 pp. 423 – 459 30.01.2014 ru 787
This article gives a review of mathematical methods of construction and using of classifications. The main approaches to solving the problems of cluster analysis and grouping are discussed. We have also proposed global and local natural classification criteria. The methods of discriminant analysis (diagnosis, pattern recognition with the teacher) are discussed in connection with the construction of generalized indicators (ratings)
256 kb

MATHEMATICAL THEORY OF RATINGS

abstract 1141510001 issue 114 pp. 1 – 26 30.12.2015 ru 894
When developing management solutions with the aim of joint consideration and comparison of various factors, partial removal of uncertainty is widely used ratings. In the theory of decisionmaking in almost the same sense, we use the terms "composite index" or "integrated indicator". The article is devoted to the mathematical theory of ratings as tools for studying socio-economic systems. We considered, primarily, linear ratings which is a linear function from a single (private) indicators (factors, criteria), constructed using the coefficients of importance (weightiness, importance). The study discusses the factors affecting the magnitude of the ratings. Three groups of causes affect the value of a line ranking: the ways of measurement of individual indicators, the choice of the set of indicators; the values of the coefficients of importance. We considered binary ratings when the rating takes two values. To compare the proposed rankings we use a new indicator of the quality of diagnostics and prognostic power. Significantly, in many managerial situations, significant differences between objects are identified using any rating. According to the fundamental results of stability theory, the same source data should be processed in several ways. Matching findings, obtained using multiple methods, likely reflect the properties of reality. The difference is the result of a subjective selection method. When using the results of the comparison of objects according to several indicators (criteria ratings), including in dynamics, very useful is the selection of the Pareto set. We discuss the examples of the application of the decision theory, expert evaluations and rankings when developing complex technical systems
284 kb

METHODOLOGY OF CONTROL PROCESSES MODELING IN SOCIO-ECONOMIC SYSTEMS

abstract 1011407011 issue 101 pp. 166 – 196 30.09.2014 ru 1213
The article introduces the basic concepts of control theory. It has also noted the multicriteriality of real control problems. After reviewing the basic concepts of the theory of modeling we have analyzed postwar history and current status of mathematical modeling of control processes. We have also discussed the modeling methodology. As an example of a real model of the management process we have considered a model of allocation of time between the acquisition of knowledge and development of skills
190 kb

METHODS OF REDUCING SPACE DIMENSION OF STATISTICAL DATA

abstract 1191605005 issue 119 pp. 92 – 107 31.05.2016 ru 289
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
240 kb

MODERN ECONOMETRIC METHODS - INTELLECTUAL TOOLS OF ENGINEERS, MANAGERS AND ECONOMISTS

abstract 1161602033 issue 116 pp. 479 – 509 29.02.2016 ru 557
Statistical methods are widely used in domestic feasibility studies. However, for most managers, economists and engineers, they are exotic. This is because modern statistical methods are not taught in the universities. We discuss the situation, focusing on the statistical methods for economic and feasibility studies, ie, econometrics. In the world of science, econometrics has a rightful place. There are scientific journals in econometrics, Nobel Prizes in Economics are awarded to series of researches in econometrics. The situation in the field of scientific and practical work and especially the teaching of econometrics in Russia is disadvantaged. Often, individual particular constructions replace econometrics in general, such as those related to regression analysis. In econometrics we select three types of scientific and applied activities: development and study of methods of applied statistics, taking into account the specifics of economic data; development and study of econometric models, in accordance with the specific needs of economic science and practice; the use of econometric methods for statistical analysis of specific economic data. This article describes these three types of scientific and applied activities. We discuss the specificity of economic data. We show the importance of economic non-numeric values. We discuss the statistics of interval data - scientific direction at the joint of metrology and statistics. We give the representation of the econometric models. Problems of application of econometric methods are considered as an example of inflation. We discuss the statistics and econometrics as the field of scientific and practical activities. We have examined econometric methods in practical and training activities
216 kb

MOVING FORWARD TO ARISTOTLE: WE MUST BE FREE FROM THE PERVERSIONS OF ECONOMIC THEORY

abstract 1271703033 issue 127 pp. 478 – 500 31.03.2017 ru 362
The founder of the economic theory is Aristotle. The so-called "market economy" is a perversion of Aristotle's views. We have to eliminate distortions. What can replace the "market economy"? We are developing a new organizational-economic theory - solidary information economy, based on the views of Aristotle. The name of this theory has changed over time. Initially, we used the term "nonformal information economy of the future", and then began to use the term "solidary information economy." In connection with Biocosmology and neo-Aristotelism preferred is an adequate term "functionalist organic information economy". This article describes the main provisions of solidary information economy, intended to replace the market economy as a management tool. The main problems are discussed, the solution of which is devoted to research related to the considered basic organizational and economic theory. We discuss Aristotle's positions, on which the economic theory is based, in particular, solidary information economy. We prove that the market economy has remained in the XIX century and the mainstream in modern economic science - justification of insolvency of a market economy and the need to move to a planned system of economic management. We examine the impact of ICT on economic activity. We develop the approaches to decision-making in the solidary information economy. On the basis of modern decision theory (especially expert procedures) and informationcommunication technologies people can get rid of chrematistics and will understand the term of "economy" according to Aristotle
286 kb

MULTIFORMITY OF OBJECTS OF NON-NUMERICAL NATURE

abstract 1021408002 issue 102 pp. 32 – 63 31.10.2014 ru 696
In accordance with the new paradigm of mathematical statistics the statistics of objects of nonnumerical nature (statistics of nonnumerical objects, non-numerical data statistics, non-numeric statistics) is one of the four main areas of mathematical statistics. Statistics of objects of nonnumerical nature consists of a central core - statistics in spaces of arbitrary nature - and statistical theories of analysis of specific types of non-numeric data. To identify possibilities of application of statistics of objects of nonnumerical nature it is useful to explore the multiformity of objects of non-numeric nature. This is the subject of this article. We have considered the results of measurements at scales other than absolute; binary relations; dichotomous (binary) data; sets. We have also analyzed the objects of non-numerical nature as statistical data, and their importance in the formation of statistical or mathematical model of a real phenomenon, as a result of data analysis
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