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
In this article we substantiate the necessity of the
development of controlling of organizational and
economic methods, including forecasting tools, the
development and management of decision-making,
and others. Controlling service is central to the
development and implementation of organizational
and economic methods to achieve the goals set by
management. However, quite often the controlling
service has a different name, justified by the history
of the organization. To resolve this paradox, we
begin with a discussion of the content of the terms
"controlling" and especially "Controlling
organizational and economic methods". We discuss
the role of "controlling service" in the management
of organizations and enterprises, as well as territorial
and municipal entities. As an example of the
controlling instrument of organizational and
economic methods is considered an automated
system of forecasting and prevention of aviation
accidents, the use in this system the expert
technologies and quantitative risk estimation
methods. We consider this system as a controlling
tool in the management of safety, while customers
and performers do not use the term "controlling" in
the official documentation of this project. In
accordance with the Presidential Decree of 21
August 2012 â„– 1199 one of the 11 integrated
indicators of the executive power is the indicator
"estimate the population of the executive
authorities." Its use in controlling in the field of
strategic management of regional and municipal
entities was proposed to carry out on the basis of
solidary information economy (the former name -
the informal information economy of the future),
developed by us from 2007. We give the basic ideas
of solidary information economy. However, the
term "controlling" is not always used in relation to
this subject. The same applies to researches related
to organizational and economic modeling of
innovation and development of innovative systems
We consider an approach to the transition from
continuous to discrete scale which was defined by
means of step of quantization (i.e. interval of
grouping). Applied purpose is selecting the number
of gradations in sociological questionnaires. In
accordance with the methodology of the general
stability theory, we offer to choose a step so that the
errors, generated by the quantization, were of the
same order as the errors inherent in the answers of
respondents. At a finite length of interval of the
measured value change of the scale this step of
quantization uniquely determines the number of
gradations. It turns out that for many issues gated it
is enough to point 3 - 6 answers gradations (hints).
On the basis of the probabilistic model we have
proved three theorems of quantization. They are
allowed to develop recommendations on the choice
of the number of gradations in sociological
questionnaires. The idea of "quantization" has
applications not only in sociology. We have noted,
that it can be used not only to select the number of
gradations. So, there are two very interesting
applications of the idea of "quantization" in
inventory management theory - in the two-level
model and in the classical Wilson model taking into
account deviations from it (shows that
"quantization" can use as a way to improve
stability). For the two-level inventory management
model we proved three theorems. We have
abandoned the assumption of Poisson demand,
which is rarely carried out in practice, and we give
generally fairly simple formulas for finding the
optimal values of the control parameters,
simultaneously correcting the mistakes of
predecessors. Once again we see the interpenetration
of statistical methods that have arisen to analyze
data from a variety of subject areas, in this case,
from sociology and logistics. We have another proof
that the statistical methods - single scientificpractical
area that is inappropriate to share by areas
of applications
The article begins with the letter of the chief
engineer of chemical plant near Moscow. He
requests to analyze of data by means of modern
statistical methods and give an opinion on the
presence (or absence) of the relationship between
the two methods of determining the viscosity of the
mastic. For each of the batches of mastic It was
presented two numbers - the viscosity measurement
results of the two methods. These numbers form two
paired samples. We want to install, give whether
two specific methods similar results. The true values
of viscosity in different batches are not equal. Their
difference is not allows us to combine the results of
the first measurement method in first sample, the
results of the second method - in the second sample,
as we can do in the case of testing the homogeneity
of two independent samples. For solutions to this
problem we discuss four statistical criterions, based
on a study of the differences between corresponding
values in two paired samples. We test the hypothesis
of equality 0 of median of these differences (sign
test) and of equality 0 of the mathematical
expectation of these differences. Hypothesis of
testing of equality of the distribution functions of
two paired samples is reduced to the hypothesis of
symmetry of the distribution function of these
differences with respect to 0. In the alternative of the
shift is proposed to use the Wilcoxon signed rank
criterion. In the total alternative is proposed to use
criterion of the omega-square type which is
developed by the author of this article
In modern conditions of quantitative and qualitative
degradation of science in general and economics in
particular, especially in our country, the scientific
direction of "Controlling" stands out not only for its
activity, but also the rapid intensive and extensive
growth. This work is the summary of the main
publications of scientific results on controlling
obtained at the Laboratory of economicmathematical
methods in controlling of Scientific
and Educational Center "Controlling and
management innovations" of Bauman Moscow State
Technical University. We discuss the concept of
"method", "tool", "mechanism", "algorithm" in
relation to the Controlling. Adequate use of these
terms is necessary for the formulation of sound
scientific results, and to provide their perception of
the scientific community. Innovations in the field of
management in industry and other sectors of the
economy based, in particular, on the use of new
adequate organizational and economic methods.
Controlling in this area - it is the development of
relevant management procedures used and the newly
established (implanted) organizational and economic
methods to the task. Development, systematization
and application of modern mathematical tools of
controlling are the main theme of our work. We
have considered the problems of controlling new
areas - controlling risks, quality controlling,
controlling organizational and economic support for
control tasks in the aerospace industry, controlling
research activities. We have also obtained new
scientific results in controlling personnel and
ecological safety controlling
Adequate and effective assessment of the efficiency, effectiveness and the quality of scientific activities of specific scientists and research teams is crucial for any information society and a society based on knowledge. The solution to this problem is the subject of scientometrics and its purpose. The current stage of development scientometrics differs greatly from his previous appearance in the open as well as paid on-line access to huge amount of detailed data on a large number of indicators on individual authors and on scientific organizations and universities. The world has well-known bibliographic databases: Web of Science, Scopus, Astrophysics Data System, PubMed, MathSciNet, zbMATH, Chemical Abstracts, Springer, Agris, or GeoRef. In Russia, it is primarily the Russian scientific citing index (RSCI). RSCI is a national information-analytical system, accumulating more than 9 million publications of Russian scientists, as well as the information about citation of these publications from more than 6,000 Russian journals. There is too much information; it is so-called "Big data". But the problem is how to make sense of these large data, more precisely, to identify the meaning of scientometric indicators) and thus to convert them into great information ("great information"), and then apply this information to achieve the objective of scientometrics, i.e. to transform it into a lot of knowledge ("great knowledge") about the specific scientists and research teams. The solution to this problem is creating a "Scientific smart metering system" based on the use of the automated system-cognitive analysis and its software tools – an intellectual system called "Eidos". The article provides a numerical example of the creation and application of Scientometric intelligent measurement system based on a small amount of real scientific data that are publicly available using free on-line access to the RSCI
In 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
In 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 economic-mathematical 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
Some estimators of the probability density function
in spaces of arbitrary nature are used for various
tasks in statistics of non-numerical data. Systematic
exposition of the theory of such estimators has been
started in our articles [3, 4]. This article is a direct
continuation of these works [3, 4]. We will regularly
use references to conditions and theorems of the
articles [3, 4], in which introduced several types of
nonparametric estimators of the probability density.
We have studied linear estimators. In this article, we
consider particular cases - kernel density estimates in
discrete spaces. When estimating the density of the
one-dimensional random variable, kernel estimators
become the Parzen-Rosenblatt estimators. Under
different conditions, we prove the consistency and
asymptotic normality of kernel density estimators.
We have introduced the concept of "preferred rate
differences" and are studied nuclear density
estimators based on it. We have introduced and
studied natural affinity measures which are used in
the analysis of the asymptotic behavior of kernel
density estimators. Kernel density estimates are
considered for sequences of spaces with measures.
We give the conditions under which the difference
between the densities of probability distributions and
of the mathematical expectations of their nuclear
estimates uniformly tends to 0. Is established the
uniform convergence of the variances. We find the
conditions on the kernel functions, in which take
place these theorems about uniform convergence. As
examples, there are considered the spaces of fuzzy
subsets of finite sets and the spaces of all subsets of
finite sets. We give the condition to support the use
of kernel density estimation in finite spaces. We
discuss the counterexample of space of rankings in
which the application of kernel density estimators
can not be correct
In the USSR higher attestation Commission from
1975 to the collapse of the USSR was subordinated
not to the Ministry of education and science, but to
the Council of Ministers of the USSR directly.
However, since then there is a steady trend of gradual
reduction of the status of the Commission. Today
it is not just included in the Ministry of education,
it is just one of the units of one of its structures:
the Rosobrnadzor. Reduced status of the HAC inevitably
leads to a decline in the status and in the adequacy
of scientific degrees assigned as well as scientific
ranks. This process of devaluation of traditional
academic degrees and titles assigned to the HAC,
has reached the point when a few years ago there
were abolished salary increments for them. Now,
instead of that, every university and research institutes
have developed their local, i.e. non-comparable
with each other scientometric methods of evaluation
of the results of scientific and teaching activities.
Despite the diversity of these techniques, there is a
common thing among all of them, which is the disproportionate
role of the h-index. The value of the
Hirsch index starts to play an important role in the
protection, when considering competitive cases for
positions, as well as in determining the monthly
rewards for the results of scientific and teaching
activities. By itself, this index is well founded, theoretically.
However, in connection with the practice
of its application in our conditions, in the collective
consciousness of the scientific community there was
a kind of mania, which the authors call the "Hirschmania".
This mania is characterized by elevated
unhealthy interest to the value of the Hirsch index,
as well as incorrect manipulation of its value, i.e.
inadequate artificial exaggeration of this value, as
well as a number of negative consequences of that
interest. In this study we have made an attempt to construct a quantitative measure for assessing the
extent of improper manipulation of the value of the
Hirsch index, and offered a science-based modification
of the h-index, insensitive (resistant) to the manipulation.
The article presents a technique for all
the numerical calculations, which is simple enough
for any author to use
We have considered the formation of the Russian
scientific school in the field of econometrics,
obtained its obtained scientific results, the
possibilities of their use in solving problems of the
economy, the organization of production and
controlling of industrial companies and
organizations, as well as in teaching. As
econometrics we consider a scientific and an
academic discipline devoted to the development and
application of statistical methods to study economic
phenomena and processes, in short, statistical
methods in economics. Therefore, we can say that a
lot of domestic books and articles, in particular, the
works by the author of this publication from the
beginning of the 70s, are the parts of econometrics.
However, in this article we consider only the works,
in the titles of which we can see the word of
"econometrics". In our country the term
"econometrics" has become popular since the mid
90s. However, many publications and training
courses are still developed in the western outdated
paradigm. They do not conform to the new paradigm
of mathematical methods of economics, the new
paradigm of applied statistics and mathematical
statistics, mathematical methods of research. Russian
science school in the field of econometrics operates
within the scientific school in the field of probability
theory and mathematical statistics based by A.N.
Kolmogorov. Russian science school is developed in
accordance with the new paradigm of mathematical
methods. It is necessary to examine the main results
of Russian scientific schools in the field of
econometrics. We present the information on the
institutional design of national scientific schools in
econometrics, in particular, on the activities of the
Institute of High Technologies statistics and
econometrics