Name
Orlov Alexander Ivanovich
Scholastic degree
•
•
•
Academic rank
professor
Honorary rank
—
Organization, job position
Bauman Moscow State Technical University
Web site url
—
Articles count: 155
Based on an objective analysis, it must be noted that
in the arsenal of managers, especially foreign ones,
there is practically no fundamentally new methods
and tools. However, promising mathematical and
instrumental methods of controlling actively
developed in our country. In the XXI century it
developed a new paradigm of mathematical methods
of economics and produced more than 10 books,
developed in accordance with this paradigm. The
new paradigm is based on the modern development
of mathematics as a whole - on the system interval
fuzzy math. The new paradigm offers tools used
non-parametric statistics, which suggest that the
distribution functions are arbitrary. In 1979 it was
allocated one of the four major areas of modern
applied statistics - statistics of objects of nonnumeric
nature (statistics of non-numeric data, nonnumeric
statistics). The other three - statistics of
random variables, multivariate statistical analysis,
statistics of random processes and time series.
Statistics of objects of non-numeric nature is central
to the modern mathematical methods of economics.
On the basis of modern information-communication
technologies we have developed a new economic
theory - solidary information economy. New
intellectual tools of controlling include an
automated system-cognitive analysis (ASA) and its
software - the system of "Eidos". 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
The mathematical theory of classification contains a large number of approaches, models, methods, algorithms. This theory is very diverse. We distinguish three basic results in it - the best method of diagnosis (discriminant analysis), an adequate indicator of the quality of discriminant analysis algorithm, the statement about stopping after a finite number of steps iterative algorithms of cluster analysis. Namely, on the basis of Neyman - Pearson Lemma we have shown that the optimal method of diagnosis exists and can be expressed through probability densities corresponding to the classes. If the densities are unknown, one should use non-parametric estimators of training samples. Often, we use the quality indicator of diagnostic algorithm as "the probability (or share) the correct classification (diagnosis)" - the more the figure is the better algorithm is. It is shown that widespread use of this indicator is unreasonable, and we have offered the other - "predictive power", obtained by the conversion in the model of linear discriminant analysis. A stop after a finite number of steps of iterative algorithms of cluster analysis method is demonstrated by the example of k-means. In our opinion, these results are fundamental to the theory of classification and every specialist should be familiar with them for developing and applying the theory of classification
Statistical methods are based on the developed theory and demonstrated its usefulness in the sectors of the economy. However, the analysis of the situation in the application of statistical methods shows obvious distress, in which accumulated in our country's scientific potential is not used to the full. As practice shows, it is not enough to develop promising modern theory-based effective mathematical and instrumental methods of controlling. For using such methods in mass, it is necessary that they would be implemented. Management of innovations, i.e. innovation management, quite rightly is currently one of the most debated sections of the economy and the organization of production, of the entire economic science in general. However, the implementation of applied statistics and other statistical methods, more generally, mathematical and instrumental methods of controlling, has its own specifics. It is considered in the article. We have highlighted the developmental vulnerabilities - low scientific level of many individuals applying statistical methods, the lack of organizational structure of applied statistics as a field of applied activities and others. We regret to note that the very idea of the need to establish requirements for the methods of data analysis and project formulations such requirements remained outside the attention of those professionals who need them and were addressed. We have no adequate system of guidance for documents on concrete statistical methods performed on modern scientific level. According to the author, the desired future of applied statistics is reorganization according to the model of Metrology. We have analyzed the application of statistical methods as a specialty. The analysis of state standards on statistical methods and the causes of them blunders are given. We have discussed the status of documents for statistical methods for standardization and quality control.
We discuss a new system of "Six Sigma" for implementation advanced mathematical and instrumental methods of controlling
Estimates of the errors of the characteristics of financial flows of investment projects are needed to make adequate management decisions, particularly in the rocket and the space industry. Organizational-economic approaches to the estimations of the feasibility of innovation-investment projects to create rocket and space technologies require intensive use of numerical characteristics of the financial flows of long-term projects of this type. In organizational-economic support for control problems in the aerospace industry we must provide the need to obtain the estimates of the errors of the characteristics of financial flows. Such estimates are an integral part of the organizational-economic support of innovation activity in the aerospace industry. They can be compared with the predictions interval, i.e. confidence estimation of predictive values. Half the length of the confidence interval is the prediction error estimate. In this article we give the new method for estimating the errors of the main characteristics of the investment projects. We focus on the net present value called NPV. Our method of estimation of errors is based on the results of statistics interval data, which is an integral part of the system fuzzy interval mathematics. We construct asymptotic theory which corresponds to small deviations of discount coefficients. The error of NPV has been found as the asymptotic notna. With up to infinitesimals of higher orders the error of NPV is a linear function of the maximum possible error of discount coefficients
According to the new paradigm of applied mathematical statistics one should prefer non-parametric methods and models. However, in applied statistics we currently use a variety of parametric models. The term "parametric" means that the probabilistic-statistical model is fully described by a finite-dimensional vector of fixed dimension, and this dimension does not depend on the size of the sample. In parametric statistics the estimation problem is to estimate the unknown value (for statistician) of parameter by means of the best (in some sense) method. In the statistical problems of standardization and quality control we use a three-parameter family of gamma distributions. In this article, it is considered as an example of the parametric distribution family. We compare the methods for estimating the parameters. The method of moments is universal. However, the estimates obtained with the help of method of moments have optimal properties only in rare cases. Maximum likelihood estimation (MLE) belongs to the class of the best asymptotically normal estimates. In most cases, analytical solutions do not exist; therefore, to find MLE it is necessary to apply numerical methods. However, the use of numerical methods creates numerous problems. Convergence of iterative algorithms requires justification. In a number of examples of the analysis of real data, the likelihood function has many local maxima, and because of that natural iterative procedures do not converge. We suggest the use of one-step estimates (OS-estimates). They have equally good asymptotic properties as the maximum likelihood estimators, under the same conditions of regularity that MLE. One-step estimates are written in the form of explicit formulas. In this article it is proved that the one-step estimates are the best asymptotically normal estimates (under natural conditions). We have found OS-estimates for the gamma distribution and given the results of calculations using data on operating time to limit state for incisors
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
Of the many urgent problems of Science about
Science, we consider methods for estimation of the
effectiveness and quality of the scientific activities
of the researcher, of the organization, of the
magazine. Performance indicators of scientific
activity are used as an important part in the
estimation of higher education institutions, the
innovative capacity of enterprises, etc. To estimate
the effectiveness of scientific activity is natural to
use intellectual tools which are well-established in
other subject areas. This will include, in particular,
the balanced scorecard, based on key performance
indicators (hence the title of this article), as well as
controlling, primarily controlling of research
activities. There are two more developed and
widely used tools for estimation the effectiveness
of the scientific activity - the scientometric
indicators and the expert estimators. Their critical
analysis is the subject of this article. Different
versions of manipulating of values of scientometric
indicators in the Russian Federation, in our
estimation, are still relatively rare. Perhaps this is
due to the relatively short period of their use in the
management of science. Since an indicator such as
citation index (the number of citations of
publications) of researcher, allows estimating its
contribution to science, the use of this
scientometric indicator for the management of
science is justified. At the same time, the number
of publications and especially h-index is not
possible to objectively estimate the effectiveness of
research activities, particularly in view of the
properties of the real bibliometric databases. Expert
procedures have several disadvantages. In this
article we discuss the real effectiveness of expert
procedures in the areas of their application, as
conferring academic degrees and elections to the
National Academy of Sciences (primarily in the
Russian Academy of Sciences). The basic
principles of expertise in these areas remain the
same for the past 70 years. Based on an analysis of
practice it is necessary to ascertain the lack of
efficacy of expert estimators in these areas.
Rationale to what has been said is given in the
article
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
The article analyzes the development of the theory
of statistical control (from the XVIII century to the
present). Prof. M.V. Ostrogradskii (1846) clearly
describes the practical needs (ie, arising from the
quality assurance of large quantities of bags of
flour or pieces of cloth), to meet whom he spent his
research. At the same time Simpson was among the
ideas of probability theory XVIII century.
Therefore prof. M.V. Ostrogradskii may be
regarded as the founder of the theory of statistical
process control (not only in our country but all over
the world). Limit theorems of probability theory
and mathematical statistics have provided a
number of asymptotic results in problems of
statistical quality control, offer based on these best
practices. However, we must find out how much
interest among specialists characteristics are
different from limit for finite sample sizes. Such
research for the synthesis algorithm control plan on
the basis of the limit average output level of defects
is made in this article, and for the synthesis
algorithm control plan on the basis of the
acceptance and the rejection levels of defects - not
yet (clarification of the conditions of applicability
of this algorithm - unsolved problem of applied
mathematics). We have briefly reviewed the
development of our researches on the statistical
control. Control units can be not only some units of
production, but also documents (with internal and
external audit), and standard units of air, water and
soil in the environmental monitoring. One of the
achievements can be regarded as the transfer of
statistical control of production for environmental
monitoring
Improvement of the organizational structures can increase the efficiency of enterprises. Controlling of personnel in companies such as "Research Institute" is a tool to support personnel decisions; it contributes to the strategic goals and tactical objectives. This article describes the main types of organizational structures, their properties, sociometric research as a tool for management, the stages of implementation of model of controlling of personnel in human resource management system for companies such as "Research Institute". Controlling of personnel is in regulation of HR processes, benchmarking, monitoring the implementation of the goals, taking into account the costs of implementing improved management systems, etc. It aims to determine the quality, efficiency and optimality of specific mechanisms, technologies and methods for the implementation of the HR function. Objectively, the volume of realization of the HR function depends on the presence of a certain quantities of material, labor, financial and other resources, on the objectives of the enterprise at different stages of the life cycle, as well as the number and qualifications of personnel. The quality of realization of the HR function depends on the level of its top-management's understanding of the importance of human resource management in the enterprise, as well as of the skill level of middle management. Controlling of HR function allows us to create an information base for effective management decisions that can help us to optimize the system of personnel management in the circumstances of the market environment, which is a necessary basis for the successful development of enterprises working in the field of high technology products and services