name
Orlov Alexander Ivanovich
Scholastic degree
•
•
•
Academic rank
professor
Honorary rank
—
Organization, job position
• Bauman Moscow State Technical University
Research interests
статистические методы, организационноэкономическое моделирование. Разработал новую область прикладной статистики — статистику объектов нечисловой природы
Web site url
—
Current rating (overall rating of articles)
0
TOP5 coauthors
Articles count: 139
Сформировать список работ, опубликованных в Научном журнале КубГАУ

ABOUT THE NEW PARADIGM OF MATHEMATICAL METHODS OF RESEARCH
01.00.00 Physicalmathematical sciences
DescriptionIn 2011 – 2015, the scientific community was represented by a new paradigm of mathematical methods of research in the field of organizational and economic modeling, econometrics and statistics. There was a talk about a new paradigm of applied statistics, mathematical statistics, mathematical methods of economics, the analysis of statistical and expert data in problems of economics and management. We consider it necessary to develop organizational and economic support for solving specific application area, such as the space industry, start with a new paradigm of mathematical methods. The same requirements apply to the teaching of the respective disciplines. In the development of curricula and working programs, we must be based on a new paradigm of mathematical methods of research. In this study, we present the basic information about a new paradigm of mathematical methods of research. We start with a brief formulation of a new paradigm. The presentation in this article focuses primarily on the scientific field of "Mathematical and instrumental methods of economy", including organizational and economic and economicmathematical modeling, econometrics and statistics, and decision theory, systems analysis, cybernetics, operations research. We discuss the basic concepts. We talk about the development of a new paradigm. We carry out a detailed comparison of the old and the new paradigms of mathematical methods of research. We give information about the educational literature, prepared in accordance with the new paradigm of mathematical methods of researches

ORGANIZATIONAL AND ECONOMIC SUPPORT OF SPACE INDUSTRY
DescriptionWe have a number of studies on the problems of the development of organizational and economic support for control tasks in the aerospace industry, primarily in the field of project management development of rocket and space technology. This article aims at summing up the preliminary results of the research cycle. Since the core funding of space activities in Russia is carried out in accordance with approved government bodies targeted programs from the state budget, among the indicators of financial and economic activities of enterprises should focus not maximize profits, and decrease costs. We must estimate of the feasibility of projects in the field of space activities, primarily on the scientific and technical feasibility and the socioeconomic needs, and resource provision. What is important is the analysis of all types of resources  material, production, human resources, time, and not just financial. As a basic organizational and economic theory we suggest the use of solidary information economy, hightech management, controlling, developed on the basis of a new paradigm of mathematical methods of economics, especially econometrics, decision theory, organizational and economic modeling. In project management to create rocket and space technology should take into account the risks of their implementation. In estimation of the feasibility of such projects there should be an analysis of risk assessment, as well as the use of modern statistical and expert methods of forecasting the dynamics of technical and economic indicators project. As practice shows, we have to develop new organizationaleconomic and economicmathematical models and methods. It is necessary to build a knowledge base in the art and to adequately fill it with modern knowledge based on scientific data of the Russian index of citing. In connection with the duration of the projects of development of rocket and space technology, we note the need to take account of inflation in the planning and evaluation of the financial and economic activities of enterprises, organizations and industry as a whole

ECOLOGICAL SAFETY: UNDERGROUND NONENVELOPED TANKS IN PERMAFROST FOR WASTE DISPOSAL DRILLING
DescriptionThe actuality of ecological issues was realized about 50 years ago. The highlight of the ecological movement to protect the environment has been, in our estimation, the United Nations Conference on Environment and Development (Rio de Janeiro, 1992), which adopted the concept of sustainable development. After 1992 the interest in ecology of broad masses was decreased slightly, although the environmental problems are not only remained, but appeared to a greater extent. However, now there is a legal basis for their decisions. Particularly, enterprises must have a certified environmental management system; otherwise they will be unable to compete in international markets. Awareness by humanity of need for environmental protection has led, in particular, to the deployment of scientific research in the field of ecological safety studies. Therefore, we have found that it is necessary and useful to report about the research of our team on this subject. Ecological security issues are highly relevant to the energy sector, in particular for gas enterprises. As an example of the new scientific results we discuss the innovative approach to the disposal of drilling waste. The basic idea  the use of underground nonenveloped tanks in permafrost soil for disposal of drilling waste. Permafrost is typically a negative impact on economic development, but in this situation it is the determining factor for a positive role, enabling lower costs to ensure ecological safety and, consequently, improve the competitiveness of domestic enterprises in the global gas market. This article is devoted to methods of dumping drilling waste and the problems that arise in their burial place. We discuss various methods of waste disposal, their advantages and disadvantages, as well as the impact on the environment

ORGANIZATIONAL AND ECONOMIC MODELING IN SOLVING PROBLEMS OF CONTROLLING
DescriptionAt the Department of "Economics and organization of production" at the end of XX  beginning of XXI centuries created the scientific school in the field of organizational and economic modeling, econometrics and statistics. The same name section of the department oversees the teaching of the relevant disciplines. The Laboratory of economic and mathematical methods in controlling of the Research and Education Center "Controlling and innovation in management" of Bauman Moscow State Technical University conducts research in this domain. This article is devoted to the activities of the scientific school, conducting research, and some of the results. We start with a discussion of the definitions of terms, which we use. Organizationaleconomic modeling  scientific, practical and academic discipline which devoted to the development, research and application of mathematical and statistical methods and models in economics and management of the national economy, especially in economics and management of industrial enterprises and their associations. The term "economicmathematical methods and models" has close content. Statistical methods in economics  the subject of econometrics, the base of which is applied statistics. Organizationaleconomic modeling and econometrics are discussed as a theoretical and practical trainings and discipline. We developed textbooks and manuals on the organizational and economic modeling, econometrics and statistics. We have conducted theoretical research and development of applications in the field of organizational and economic modeling. In particular, the prediction is regarded as one of the management functions in industry. We study the problem of stability in the models and methods of development of strategy of the enterprise. For prospective organizational and economic mechanisms of management of industrial and economic activities, we proposed design based on solidary information economy

MANAGEMENT PROBLEMS IN SMALL PRODUCTION COMPANIES AT EARLY LIFECYCLE STAGES
DescriptionIn 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 2530 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  AllUnion Center of statistical methods and Informatics of Central Board of the AllUnion economic society (now  Institute of high statistical technologies and econometrics of Bauman Moscow State Technical University)

ASYMPTOTICS OF ESTIMATES OF PROBABILITY DISTRIBUTION DENSITY
01.00.00 Physicalmathematical sciences
DescriptionNonparametric estimates of the probability distribution density in spaces of arbitrary nature are one of the main tools of nonnumerical statistics. Their particular cases are considered  kernel density estimates in spaces of arbitrary nature, histogram estimations and FixHodgestype estimates. The purpose of this article is the completion of a series of papers devoted to the mathematical study of the asymptotic properties of various types of nonparametric estimates of the probability distribution density in spaces of general nature. Thus, a mathematical foundation is applied to the application of such estimates in nonnumerical statistics. We begin by considering the mean square error of the kernel density estimate and, in order to maximize the order of its decrease, the choice of the kernel function and the sequence of the blur indicators. The basic concepts are the circular distribution function and the circular density. The order of convergence in the general case is the same as in estimating the density of a numerical random variable, but the main conditions are imposed not on the density of a random variable, but on the circular density. Next, we consider other types of nonparametric density estimates  histogram estimates and FixHodgestype estimates. Then we study nonparametric regression estimates and their application to solve discriminant analysis problems in a general nature space

THE LIMIT THEORY OF THE SOLUTIONS OF EXTREMAL STATISTICAL PROBLEMS
01.00.00 Physicalmathematical sciences
DescriptionMany procedures of applied mathematical statistics are based on the solution of extreme problems. As examples it is enough to name methods of least squares, maximum likelihood, minimal contrast, main components. In accordance with the new paradigm of applied mathematical statistics, the central part of this scientific and practical discipline is the statistics of nonnumerical data (it is also called the statistics of objects of nonnumerical nature or nonnumeric statistics) in which the empirical and theoretical averages are determined by solving extreme problems. As shown in this paper, the laws of large numbers are valid, according to which empirical averages approach the theoretical ones with increasing sample size. Of great importance are limit theorems describing the asymptotic behavior of solutions of extremal statistical problems. For example, in the method of least squares, selective estimates of the parameters of the dependence approach the theoretical values, the maximum likelihood estimates tend to the estimated parameters, etc. It is quite natural to seek to study the asymptotic behavior of solutions of extremal statistical problems in the general case. The corresponding results can be used in various special cases. This is the theoretical and practical use of the limiting results obtained under the weakest assumptions. The present article is devoted to a series of limit theorems concerning the asymptotics of solutions of extremal statistical problems in the most general formulations. Along with the results of probability theory, the apparatus of general topology is used. The main differences between the results of this article and numerous studies on related topics are: we consider spaces of a general nature; the behavior of solutions is studied for extremal statistical problems of general form; it is possible to weaken ordinary requirements of bicompactness type by introducing conditions of the type of asymptotic uniform divisibility

THE PROBLEM OF RESEARCH OF FINAL RANKING FOR GROUP OF EXPERTS BY MEANS OF KEMENY MEDIAN
01.00.00 Physicalmathematical sciences
DescriptionIn various applications, it is necessary to analyze several expert orderings, i.e. clustered rankings objects of examination. These areas include technical studies, ecology, management, economics, sociology, forecasting, etc. The objects can be some samples of products, technologies, mathematical models, projects, job applicants and others. In the construction of the final opinion of the commission of experts, it is important to find clustered ranking that averages responses of experts. This article describes a number of methods for clustered rankings averaging, among which there is the method of Kemeny median calculation, based on the use of Kemeny distance. This article focuses on the computing side of the final ranking among the expert opinions problem by means of median Kemeny calculation. There are currently no exact algorithms for finding the set of all Kemeny medians for a given number of permutations (rankings without connections), only exhaustive search. However, there are various approaches to search for a part or all medians, which are analyzed in this study. Zhikharev's heuristic algorithms serve as a good tool to study the set of all Kemeny medians: identifying any connections in mutual locations of the medians in relation to the aggregated expert opinions set (a variety of expert answers permutations). Litvak offers one precise and one heuristic approaches to calculate the median among all possible sets of solutions. This article introduces the necessary concepts, analyzes the advantages of median Kemeny among other possible searches of expert orderings. It identifies the comparative strengths and weaknesses of examined computational ways

STATE AND PROSPECTS OF APPLIED AND THEORETICAL STATISTICS
01.00.00 Physicalmathematical sciences
DescriptionThe 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 abovedescribed 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 midtwentieth century. The article analyzes the postwar development of the national statistics. We have identified five "growth points": nonparametrics, robustness, bootstrap, statistics of interval data, and statistics of nonnumeric 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

ECONOMETRICS AS AN ACADEMIC DISCIPLINE
01.00.00 Physicalmathematical sciences
DescriptionStatistical methods are widely used in domestic feasibility studies. However, for most managers, economists and engineers, they are exotic. This is due to the fact that 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 given 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. The article is devoted to econometrics as an academic discipline. Our course begins with a discussion of the structure of modern econometrics, the connections between applied statistics and econometric methods. We consider sample researches (analysis of surveys results), the elements of econometrics numbers, and methods of testing of statistical hypothesis about homogeneity. We have given the concepts of regression analysis, econometric classification methods, modern measurement theory. The important places are occupied by the statistics of nonnumerical data (including fuzzy sets and their links with random sets) and the statistics of interval data. The problem of the stability of statistical procedures with respect to the tolerances of input data and model prerequisites is discussed. The representations of the econometric methods of expert research and quality control, analysis and forecasting of time series, econometrics of forecasting and risks are given