=Paper= {{Paper |id=Vol-3887/paper19 |storemode=property |title=Formation of an Information Resource Based on Various Sources in Organizational Management System |pdfUrl=https://ceur-ws.org/Vol-3887/paper19.pdf |volume=Vol-3887 |authors=Oleh Andriichuk,Volodymyr Yuzefovych,Yevheniia Tsybulska,Nikolai Stoianov |dblpUrl=https://dblp.org/rec/conf/its2/AndriichukYTS23 }} ==Formation of an Information Resource Based on Various Sources in Organizational Management System== https://ceur-ws.org/Vol-3887/paper19.pdf

Oleh Andriichuk1,2,3, Volodymyr Yuzefovych 1,3, Yevheniia Tsybulska1, Nikolai Stoianov4
1
Institute for Information Recording of the National Academy of Sciences of Ukraine, Kyiv, Ukraine
2
Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
3
National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine
4
Professor Tsvetan Lazarov Bulgarian Defense Institute, Sofia, Bulgaria

Abstract
The peculiarities of obtaining and processing knowledge of different types of specialists as sources of
information for organizational management systems are considered in the paper. The mathematical
apparatus of fuzzy logic and decision support for use in organizational management systems in the formation
of information resources is proposed. A practical example of computations based on the built model
(hierarchy of goals) - the knowledge base in the decision support system is presented.

Keywords
organizational management system, information resource, analyst, expert, fuzzy logic, method of targeted
dynamic evaluation of alternatives 1

1. Introduction
According to a study [1], the largest percentage of organizational knowledge (about 42%) is in the
minds of specialists. One of the features of organizational management systems (OMS) is the presence
of human factor influences within the object and subject of management [2, 3]. Along with objective
information (e.g., instrument readings), 5 categories of specialists are also widely used as sources of
information in OMS [2]: "source" analysts, analysts for aggregation (generalization) of information to
support decision-making at different levels of management, experts, organizers of expertise and
knowledge engineers. Thus, an urgent task is to develop a mathematical apparatus for the OMS,
which will allow to use qualitatively the knowledge of all these categories of specialists about the
formation of an information resource by taking into account their characteristics.

2. Formation of an information resource of the OMS considering the
peculiarities of expert knowledge
The activities of the OMS specialists involved at different levels in the processes of generating,
processing (aggregating) and analyzing information (data) let’s call as analytical activities. To achieve
the purpose of this paper, it is necessary to identify and analyze the types of analytical activities
characteristic of different hierarchical levels of the OMS.
In [1], a generalized scheme for the formation of an information resource of a certain OMS is
presented, which, after shifting the emphasis to determine the place of analytical activities of
personnel in it, looks like as one shown in Fig.1. Analysis of Fig. 1 shows that at least five types of
analytical activities and, accordingly, groups of specialists can be distinguished within the framework
of the OMS.

ITS-2023: Information Technologies and Security, November 30, 2023, Kyiv, Ukraine
andriichuk@ipri.kiev.ua (O. Andriichuk); uzefv71@gmail.com (V. Yuzefovych);
evts68@gmail.com (Ye. Tsybulska); n.stoianov@di.mod.bg (N. Stoianov)
0000-0003-2569-2026 (O. Andriichuk); 0000-0002-6336-9548 (V. Yuzefovych);
0000-0003-3342-4507 (Ye. Tsybulska); 0000-0002-4953-4172 (N. Stoianov)
© 2023 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

CEUR
ceur-ws.org
215
Workshop ISSN 1613-0073
Proceedings
Figure 1: Scheme of formation of the OMS information resource

A "source" analyst is an analyst who carries out his/her analytical activities within one element of
the OMS based on direct observations of indicators characterizing the state of the relevant element
of the system and/or data on monitoring of environmental factors. As a result, such an analyst forms
judgments about the state of the system element or the state of individual processes and phenomena
observed in the external environment of the OMS functioning, based on his or her own ideas and
experience. As a rule, such judgments are formed by determining one of the possible states of an
element (or a component of the external environment) from a set of predefined states. The judgments
of "source" analysts are mainly based on objective observation (monitoring) data, but the source data
contain subjective distortions of information as a result of cognitive activity.
The second group includes aggregation analysts, who carry out analytical activities by generalizing
(integrating) data (information) from "source" analysts. They form judgments about the state of
different subsystems or groups of elements of the OMS and, accordingly, are mostly based on
subjective data. Since different subsystems can be distinguished within different OMS and
hierarchical links between them are possible, it is obvious that the activities of such analysts form a

216
hierarchical procedure of aggregating information with obtaining judgments on the state of
subsystems (state of the environment) of varying degrees of generalization. As a result, the subjective
distortions contained in the initial judgments (results of analytical activities) may increase due to the
imposition of their own cognitive distortions on the cognitive distortions of the "source" analysts. As
a result, the information uncertainty about the actual state of the phenomena being analyzed may
increase.
Reducing the cognitive distortions of information that are characteristic of the two groups of
experts can be ensured by formalizing the process of obtaining and aggregating it to the maximum
extent possible, as well as by jointly processing duplicate information from several analysts. For such
information processing, tools developed within the framework of fuzzy set theory and fuzzy logic,
which were specifically designed to work with expert judgments, can be effectively used. The second
way is to reduce the workload on one analyst, taking into account the psychophysiological limitations
of a person through the rational distribution of functional tasks among analysts.
Knowledge engineers and organizers of the examination must first familiarize themselves with the
relevant subject area before building the knowledge base. For this purpose, they mostly use available
open sources (the Internet, articles, lectures, ets), as well as specialized tools, such as content
monitoring systems (CMSs). In this case, the cognitive bias "the effect of the illusion of truth" may be
triggered [2]. Thus, it is inappropriate to form expert opinions in the OMS based directly on data from
popular sources. It is more reasonable to use formalized methods of processing incomplete expert
information when conducting an expert assessment. In addition, the expert evaluation organizer
selects a group of experts with a sufficient level of competence in the subject area, and further work
on building the LR takes into account the level of competence of the expert in each of the expert
evaluation issues. In this case, a cognitive bias may be triggered - the Dunning-Kruger effect [2].
Experts decompose the subject area, divide the goals into sub-goals, determine the criteria and
factors that directly affect the outcome of the examination. This process is characterized by the
following cognitive distortions: the Ringelman effect, the "focusing" effect, the "survivor's error", and
the "bicycle shed" effect [2]. To avoid them, it is advisable to use systems for distributed collection
and processing of expert information in the work of an expert group. Expert evaluation aims to
reliably determine the degree of preference between alternatives/criteria. Direct scoring and pairwise
comparisons are possible. The following cognitive biases should be avoided: the distinction error, the
anchoring effect, and the contrast effect [2]. You should also take into account George Miller's
research [3] on the limitations of human short-term memory.

3. Aggregation of analysts' knowledge
Here are the heuristic requirements for aggregating data from analysts, which, unlike data from
technical sources, are additionally characterized by varying degrees of reliability.
1. If different data is received from the same analyst during the same management cycle, the
data is not combined and only the last value of the indicator is considered
2. If several analysts send same data messages with different degrees of reliability (confidence
in their truth), the result of their combination should be characterized by greater reliability than
each individual message
3. If several analysts provide data that does not match in content, the result of combining them
should be characterized by no more reliability than the highest "declared" reliability in the
messages
4. If the content of the data provided by the analysts differs significantly, there should be a
growing possibility that the indicator actually has a different, "intermediate" value that averages
the data in some way, giving more credibility to the value that tends to be more reliable than the
"input" message.
In this case, each message about the value of the indicator is formalized as a fuzzy set:

217
𝑆 = {𝜇 (𝑥 )/𝑥 }, 𝑥 ∈ 𝑋 (1)
where 𝜇 (𝑥 ) = [0,1] – is the degree of belonging of the value 𝑥 to the fuzzy set 𝑆
𝑋 = {𝑥 , 𝑥 , … , 𝑥 } is a crisp set that is a carrier of the fuzzy set and contains N possible (valid) values
of the indicator.
For the final formalization of the message about the value of the indicator in the form of a fuzzy
set, in addition to the indicator carrier set, it is desirable to specify the degrees of membership (𝑥 )
for each of the possible values in the form of a functional dependence. There are many different ways
to define a membership function for fuzzy sets, the simplest of which is a triangular function, which
is described as follows:
0, 𝑖𝑓 𝑥 ≤ 𝑎;
⎧(𝑥
− 𝑎)
⎪ , 𝑖𝑓 𝑥 < 𝑥 < 𝐶;
⎪ (𝐶 − 𝑎)
𝜇 (𝑥 ) = (𝑏 − 𝑥 ) (2)
⎨ , 𝑖𝑓 𝐶 ≤ 𝑥 < 𝑏;
(𝑏
⎪ − 𝐶)
⎪ 0, 𝑖𝑓 𝑥 ≥ 𝑏.
⎩
where C is the value of the indicator determined by the analyst; a, b are the left and right
boundaries of the triangular membership function, which applies to other values of the indicator
other than C that are between a and b.
If |𝐶 − 𝑎| = |𝐶 − 𝑏|, the membership function is symmetric with respect to C. The range of values
of the indicator ∆ = |𝑏 − 𝑎| determines the list of its values close to C, which the indicator may
actually take. The membership function can be viewed as an analogy to the distribution of the
measurement error of an indicator by any technical means, where the value C is the measurement
result, ∆ /2 is the absolute measurement error, and the membership function 𝜇 (𝑥 ) is the law of
error distribution.
To take into account the reliability of the message, it is necessary to set a numerical
correspondence (scale) to the defined linguistic values of reliability (confidence in the value of the
indicator). An example of such correspondence is shown in Table 1.

Table 1
Linguistic meanings of the confidence attribute and their corresponding numerical values
The linguistic meaning of The numerical value of the
the attribute of confidence confidence attribute (Ds)
"Reliable" 1
"Probably" 0,7
"Maybe" 0,5
"Doubtful" 0,25

In the next all the values of the membership function are normalized by the corresponding
numerical value of the confidence in the expression:
𝜇 (𝑥 ) = 𝐷 ∗ 𝜇 (𝑥 ). (3)
Since this transformation of the independence function is linear, it will retain its triangular shape.
Having carried out the specified simple formalization of all incoming messages from analysts, you
can proceed to solving the problem of their unification. Within the framework of the theory of fuzzy
sets, a significant toolkit for working with fuzzy sets has been accumulated. The operation of the
algebraic sum of fuzzy sets best corresponds to the unification rules formulated above. To combine
two messages A and B, the corresponding expression would look like this:
𝜇 (𝑥 ) = 𝜇 (𝑥 ) + 𝜇 (𝑥 ) − 𝜇 (𝑥 ) ∗ 𝜇 (𝑥 ). (4)
The last operation is to obtain the combined value of the indicator and determine its reliability,
for which the expression for obtaining the weighted average of the fuzzy set 𝜇 (𝑥 ) can be used:

218
∑ 𝑥 ∙𝜇 (𝑥 )
В
(5)
𝑥 = .
∑ 𝜇 В (𝑥 )
This operation is called defuzzification of a fuzzy set. The reliability of the resulting value will be
determined by the degree of membership of the weighted average obtained:
𝐷 =𝜇 𝑥 . (6)
The proposed approach will reduce the influence of the subjective component on the result of data
processing from analysts.

4. Aggregation of experts' knowledge
When forming the information resource of the OMS, certain features of expert knowledge should also
be taken into account [6]. During the expert evaluation, cognitive distortions of data and knowledge
may occur, which significantly affect its result. Human psychophysiological limitations limit the
ability to process more than 9 objects at the same time [3]. Expert evaluation is time-consuming and
costly, so it should be used only when absolutely necessary. If possible, it is recommended to use
previously built knowledge bases (KBs), their fragments and templates (precedents) for solving
similar problems in retrospect. Experts may miss assessment sessions, not answer some questions
due to limited time, busy schedule, fatigue or unwillingness. Therefore, it is important to be able to
process incomplete expert information [7]. At the same time, the need for generalized and
systematized knowledge is gradually revealed through decomposition at smaller levels of the OMS
hierarchy, and detailed information is aggregated from the bottom up to meet the information needs
of users at higher management levels.
To aggregate expert knowledge, the method of goal dynamic evaluation of alternatives (MGDEA)
[8, 9] is used for processing of a hierarchy of goals [10]. The hierarchy is the result of decomposition
of the main goal into components (subgoals), which, in turn, are also decomposed into subgoals, etc.
The decomposition process stops when we get specific activities (projects) as components.
The MGDEA offers a generalized procedure for determining the degree of achievement of any
hierarchy goal at a given time t. To determine the degree of achievement of a particular goal, it is
necessary to analyze the degree of achievement of the goals that directly affect this goal for each
subset of compatible goals [8]. Thus, the degree of achievement of the h-th goal at time t is described
by the formula for di (t):
0, 𝑖𝑓 𝐷 (𝑡) < 𝑇 ,
⎧
⎪ 𝑇 , 𝑖𝑓 𝐷 (𝑡) = 𝑇 ,
𝑑 (𝑡) = 𝑓 𝐷 (𝑡) , 𝑖𝑓 𝑇 < 𝐷 (𝑡) < 1 − ∑ 𝑤 ( ) , (7)
⎨
⎪ ( )
⎩ 1, 𝑖𝑓 1 − ∑ 𝑤 ≤ 𝐷 (𝑡) ≤ 1,
( )
where 𝐷 (𝑡) = sup ∑ 𝑤 𝑑 (𝑡);Ti – is the threshold for achieving the i-th goal; 𝑓(𝐷 (𝑡)) – is a
( )
function of the degree of achievement of the i-th goal at time t; 𝑤 𝑤 – is partial coefficients of
influence of the j-th goal in the k-th group of compatible goals, which has a negative impact on the i-
th goal.

5. A practical example
As a practical example, the proposed mathematical tools were used to build the knowledge base of
the Energy Security Strategy of Ukraine [11]. The results confirmed the applicability of the proposed
approach to solving such problems.
In Fig. 2 shows an example of goals’ hierarchy built by means of the Solon-3 Decision Support
System (DSS) [12].

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Figure 2: Structure of the goal hierarchy

Below is a list of the hierarchy's goal statements and their corresponding numbers in the goal
hierarchy structure (Figure 2):
No. 0 - Energy security of Ukraine
No. 1 - Availability of energy sources and energy resources of all types for consumers
No. 2 - Sustainability of the energy sector
No. 3 - Economic efficiency of the energy sector, energy supply systems and import substitution
of mineral raw materials
No. 4 - Energy efficiency of energy resources use and energy efficiency of the national economy
No. 5 - Environmentally acceptable impact of energy on the environment
No. 6 - Integration of the energy sector into the EU's political, technological, technical, economic
and legal space
No. 7 - Independence of the state in the formation and implementation of domestic and foreign
policy in the energy sector, ensuring the realization of national interests
No. 8 - Development of scientific, technical, innovative and educational potential of Ukraine for
the needs of the energy sector

220
No. 9 - Improvement of the technical condition of end-user energy supply systems
No. 10 - Preventing the deepening of energy poverty and increasing the share of household
expenditures on energy supply
No. 11 - Improving mechanisms for supporting certain categories of consumers and eliminating
cross-subsidization in energy markets
No. 12 - Introduction of simplified procedures and guarantee of non-discriminatory connection of
consumers and other users to the energy supply networks
No. 13 - Stimulating the development of energy exchange trading
No. 14 - Implementation of an effective mechanism for informing household consumers about
comparative prices and opportunities to change suppliers
No. 15 - Implementation of a data management system based on big data, digitalization of
processes, creation of convenient services for citizens
No. 16 - Ensuring cybersecurity and physical security of critical infrastructure in the energy sector
No. 17 - Implementation of a system for conducting risk assessments and exchanging information
on risks and threats to critical infrastructure of the energy sector
No. 18 - Formation of a system for preventing the realization of threats of any type and responding
to crisis situations, implementation of the energy sustainability plan of Ukraine
No. 19 - Ensuring a balanced development of energy supply systems, taking into account the
uneven consumption and operation of individual energy producers
No. 20 - Development of territorial communities' capacities for self-sufficiency in the conditions
of disruption of the national energy supply systems
No. 21 - Formation of a system of minimum stocks of energy resources and critical energy
equipment
No. 22 - Introduction of a mechanism for cooperation and interaction between the state and
operators of critical infrastructure in the energy sector in case of crisis, in particular, to involve state
representatives in participation and control over the implementation of crisis response plans
No. 23 - Adaptation of the energy sector to the negative impact of climate change
No. 24 - Introduction of efficient energy markets, ensuring transparency of their functioning and
regulation, increasing the capitalization of energy companies, and developing the exchange trading
system
No. 25 - Renewal of fixed assets of the energy sector, in particular by creating favorable conditions
for the introduction of mechanisms to support the implementation of large-scale investment projects
for the development of critical infrastructure in the energy sector
No. 26 - Stimulating competition in energy markets, in particular by strengthening antitrust
legislation and developing mechanisms of state influence on market participants that violate antitrust
laws and/or license conditions
No. 27 - Stimulating import substitution, in particular through the development of bioenergy, wind
energy, and a reasonable increase in energy production
No. 28 - Improving corporate governance, stimulating the attraction of highly qualified personnel
No. 29 - Implementation of a set of measures and programs to improve energy efficiency by sectors
of the national economy, in particular in the fuel and energy complex, as well as in the housing and
communal sector, households and the public sector
No. 30 - Introduction of the principle of "energy efficiency first" for government and business
decision-making
No. 31 - Simplification of procedures and development of services for the implementation of
energy efficiency projects
No. 32 - Ensuring the accounting of energy consumption
No. 33 - Implementation of a set of measures to expand the use of local alternative fuels

221
No. 34 - Development of a set of measures for the integration of consumers using renewable
energy sources for their own consumption into the operation of the Integrated Energy System of
Ukraine
No. 35 - Formation of an institutional framework to ensure access to high-quality energy audits
and promote the implementation of energy management programs
No. 36 - Optimization and determination of the mechanism for financing measures for the
greening of coal-fired generating facilities
No. 37 - Significant reduction of greenhouse gas emissions from the activities of fuel and energy
enterprises, promotion of the replacement of traditional fuels in transport with electricity and biofuels
No. 38 - Implementation of a reasonable increase in the share of renewable energy sources, taking
into account the requirements for ensuring the operational security of energy supply systems and the
impact on the price parameters of the energy market
No. 39 - Implementation of measures to clean up coal-fired generating facilities in order to
preserve the medium-term prospects for competitive development of electricity generation based on
the use of domestic energy resources
No. 40 - Development and implementation of a long-term program for the replacement of coal-
fired generating facilities
No. 41 - Bringing Ukrainian legislation in line with EU law (EU acquis) to create common energy
markets
No. 42 - Termination of electricity imports from the Russian Federation and the Republic of
Belarus and testing of the integrated power system of Ukraine in the mode of separate operation
during 2022
No. 43 - Physical separation from the power grids of the Russian Federation and the Republic of
Belarus
No. 44 - Synchronization of the operating modes of the Integrated Power System of Ukraine and
the European Network of Transmission System Operators for Electricity
No. 45 - Implementation of economically feasible projects for the expansion of cross-border
interconnectors between Ukraine and the EU countries
No. 46 - Formation of a system for harmonizing the goals of development of the national economy
and the fuel and energy complex with the priorities of ensuring national security and realization of
national interests
No. 47 - Preventing Ukraine's increasing dependence on external suppliers, ensuring an
appropriate level of diversification of energy resources and technologies, in particular through
economically justified growth of the share of renewable energy sources and local sources
No. 48 - Economically justified growth of natural gas, oil and other energy resources production
No. 49 - Increasing the share of localization of equipment production for the fuel and energy
sector, in particular for nuclear power, hydropower, renewable energy, and heat power
No. 50 - Implementation of effective mechanisms of public-private partnership to ensure energy
security
No. 51 - Establishment of a permanent Ukraine-EU and Ukraine-NATO format to discuss regional
energy security issues
No. 52 - Creation of a regulatory framework and development of an action plan for the return of
assets and resources of the fuel and energy sector that were seized as a result of the temporary
occupation of part of the territory of Ukraine by the Russian Federation
No. 53 - Setting priorities and coordinating foreign economic cooperation to support the
competitiveness of the Ukrainian energy sector in global markets, diversification of energy sources
and supply routes
No. 54 - Meeting the needs of current and future generations to ensure the use of the latest energy
technologies, including hydrogen energy

222
No. 55 - Introduction of a mechanism for the use of budget funds and other sources of financing
for technological innovation changes in the energy sector
No. 56 - Development and transfer of technologies that help to solve current global environmental
challenges, mainly caused by climate change and the impact of energy on the environment
No. 57 - Consumer-oriented educational activities and promotion of the latest technological know-
how and energy-efficient technologies among the general public
No. 58 - Creating conditions for the involvement of new types of energy resources and energy
sources in the updated energy balance based on the principle of self-sufficiency, increasing the choice
of energy types that will contribute to the formation of an updated energy balance and self-sufficiency
in energy resources
No. 59 - Application of the latest technological solutions to improve the technical characteristics
of nuclear power plants subject to unconditional compliance with all requirements for safe operation
of nuclear facilities
No. 60 - Scaling up the successful experience of scientific and innovative pilot projects, in
particular for the transformation of coal regions and reform of the coal sector
No. 61 - Determination of priorities of the state technical policy in the energy sector
No. 62 - Modernization of the personnel training system for the energy sector by introducing new
specialties and retraining programs in accordance with the needs of the fuel and energy complex
No. 63 - Cyber threats / cyber incidents against critical infrastructure in the energy sector
No. 64 - Influence of pressure groups on the energy sector
No. 65 - Resistance to the introduction of European rules for the transparent functioning of energy
markets
No. 66 - Blocking the supply of necessary resources and equipment for the energy sector of
Ukraine
No. 67 - Personnel shortage (loss of qualified personnel and the system of training/retraining)
No. 68 - Increased depreciation of fixed assets of energy infrastructure facilities
No. 69 - Failure to comply with the requirements and measures to interconnect Ukraine's systems
(networks) with the EU electricity and gas supply systems, including the expansion of the capacity of
interstate crossings (interconnectors)
No. 70 - Absence of a system of strategic planning and coordination of economic and energy
development
No. 71 - Threats to the physical security of energy infrastructure facilities
No. 72 - Uncontrolled change in the structure of generating capacities
No. 73 - Lack of energy reserves
No. 74 - Lack of capacity for "crisis" response
No. 75 - Increased deficit of capital investments in energy development
No. 76 - The ongoing armed aggression of the Russian Federation against Ukraine
No. 77 - Low energy efficiency of the national economy
No. 78 - Continued shadowing of relations in the energy sector, in particular through improper
accounting of resources
No. 79 - Imperfection of legislation on energy market regulation (preservation of the subsidy
system, the mechanism of public special obligations or restrictions on the rights of certain energy
market participants)
No. 80 - The impact of climate change on the structure and modes of energy consumption
No. 81 - Obstruction by the Russian Federation of the interconnection of Ukraine's systems
(networks) with the EU electricity and gas supply systems
No. 82 - Failure to adopt legislation necessary for the implementation of energy rules in
accordance with the provisions of EU law (EU acquis)
No. 83 - Deepening of energy poverty, increase in household energy costs
No. 84 - Insufficient level of competition and regulation of monopolies in energy markets

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No. 85 - Delays in the adoption and implementation of decisions on the refusal to use coal for
energy needs
No. 86 - Inefficiency of technologies and technological processes of energy market participants
No. 87 - High level of industrial emissions and wastewater from the fuel and energy sector
No. 88 - High level of greenhouse gas emissions from the fuel and energy sector
No. 89 - High carbon intensity of final energy consumption
No. 90 - Loss of scientific and technical potential of the energy sector
No. 91 - Lack of development of corporate management, inefficient operation of fuel and energy
enterprises in market conditions
No. 92 - Bringing coal production volumes in line with the needs of Ukraine's energy sector on the
basis of market principles of management and competition with the determination of the term of coal
use for energy needs.
Table 1 shows the threat numerical rating computed using the Solon-3 DSS.

Table 2
Rating of threats to Ukraine's energy security for pessimistic, probable and optimistic scenarios
No. of goals Pessimistic scenario Probable scenario Optimistic scenario
in the
Rank The value of Rank The value of Rank The value of
hierarchy
potential potential potential
efficiency efficiency efficiency
70 1 0,13758 1 0,13828 2 0,14156
76 2 0,10562 2 0,11900 1 0,14459
75 3 0,09779 4 0,10063 4 0,08592
78 4 0,09656 3 0,10572 3 0,11246
64 5 0,06934 5 0,08115 5 0,07582
77 6 0,05879 6 0,06578 6 0,07245
90 7 0,05348 7 0,05534 8 0,04557
84 8 0,04891 10 0,03376 11 0,02886
71 9 0,04805 8 0,05433 7 0,06628
86 10 0,02949 9 0,03404 9 0,03768
63 11 0,02948 12 0,02655 16 0,01276
68 12 0,02764 11 0,02967 10 0,03062
81 13 0,02302 23 0,00611 24 0,00427
74 14 0,01794 14 0,01664 15 0,01356
83 15 0,01734 15 0,01655 13 0,01492
91 16 0,01719 13 0,01806 12 0,01874
82 17 0,01620 21 0,01000 22 0,00861
73 18 0,01553 16 0,01400 17 0,01272
65 19 0,01330 25 0,00351 26 0,00245
72 20 0,01094 18 0,01217 18 0,01218
67 21 0,01077 19 0,01130 20 0,01006
79 22 0,01058 17 0,01384 14 0,01479
66 23 0,01035 27 0,00239 27 0,00144
89 24 0,00983 20 0,01068 19 0,01146
85 25 0,00878 22 0,00926 21 0,00922
69 26 0,00654 28 0,00185 28 0,00125
88 27 0,00512 24 0,00552 23 0,00590
87 28 0,00261 26 0,00282 25 0,00295
80 29 0,00127 29 0,00106 29 0,00092

224
Conclusions
The article shows the peculiarities of knowledge of analysts and experts, which are typical for OMS,
which further form the information basis of databases and KBs in the formation of the OMS
information resource. Five types of specialists (sources of information in the OMS) are assigned.
Using the fuzzy logic apparatus to process information from "source" analysts and aggregation
analysts in the information-analytical subsystem of the OMS is proposed.
Using information received from analysts after its preliminary processing along with objective
and expert information when building the KB of the decision support subsystem of the OMS is
suggested.

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