Інтелектуальні системи підтримання прийняття рішень у розвитку інфраструктури мегаполісу
From the point of view of the management theory, a megapolis is a complex non-stationary spatial system. The problem of making innovative decisions on the development of their infrastructure is caused by the presence of a large amount of information, its uncertainty and inconsistency. This article d...
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The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2022
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| author | Trofymchuk, Oleksandr Stenin, Aleksandr Soldatova, Maria Drozdovich, Irina |
| author_facet | Trofymchuk, Oleksandr Stenin, Aleksandr Soldatova, Maria Drozdovich, Irina |
| author_institution_txt_mv | [
{
"author": "Oleksandr Trofymchuk",
"institution": "Institute of Telecommunications and Global Information Space of NAS of Ukraine, Kyiv"
},
{
"author": "Aleksandr Stenin",
"institution": "National Technical University of Ukraine \"Igor Sikorsky Kyiv Polytechnic Institute\", Kyiv"
},
{
"author": "Maria Soldatova",
"institution": "National Technical University of Ukraine \"Igor Sikorsky Kyiv Polytechnic Institute\", Kyiv"
},
{
"author": "Irina Drozdovich",
"institution": "Institute of Telecommunications and Global Information Space of NAS of Ukraine, Kyiv"
}
] |
| author_sort | Trofymchuk, Oleksandr |
| baseUrl_str | http://journal.iasa.kpi.ua/oai |
| collection | OJS |
| datestamp_date | 2022-10-17T22:12:39Z |
| description | From the point of view of the management theory, a megapolis is a complex non-stationary spatial system. The problem of making innovative decisions on the development of their infrastructure is caused by the presence of a large amount of information, its uncertainty and inconsistency. This article discusses the principles of building intelligent decision support systems of a situational type for the innovative development of the infrastructure of megacities. Solutions are formed by logico-analytical processing of data on the situation in general and special cases of situations for the considered subject of the megalopolis infrastructure. For the practical implementation of the decision-making mechanism, the article proposes a linguistic-numerical method for determining the potentially best alternative and a fuzzy situational algorithm for managing the subjects of the megalopolis infrastructure, based on the structural generality of the situations of a fuzzy situational network. The obtained results were tested on two real infrastructure subjects of Kyiv. |
| doi_str_mv | 10.20535/SRIT.2308-8893.2022.2.04 |
| first_indexed | 2025-07-17T10:27:57Z |
| format | Article |
| fulltext |
O. Trofymchuk, A. Stenin, M. Soldatova, I. Drozdovich, 2022
Системні дослідження та інформаційні технології, 2022, № 2 61
TIДC
ПРОБЛЕМИ ПРИЙНЯТТЯ РІШЕНЬ ТА
УПРАВЛІННЯ В ЕКОНОМІЧНИХ, ТЕХНІЧНИХ,
ЕКОЛОГІЧНИХ І СОЦІАЛЬНИХ СИСТЕМАХ
UDC 004.738
DOI: 10.20535/SRIT.2308-8893.2022.2.04
INTELLIGENT DECISION SUPPORT SYSTEMS IN THE
DEVELOPMENT OF MEGALOPOLIS INFRASTRUCTURE
O. TROFYMCHUK, A. STENIN, M. SOLDATOVA, I. DROZDOVICH
Abstract. From the point of view of the management theory, a megapolis is a com-
plex non-stationary spatial system. The problem of making innovative decisions on
the development of their infrastructure is caused by the presence of a large amount
of information, its uncertainty and inconsistency. This article discusses the princi-
ples of building intelligent decision support systems of a situational type for the in-
novative development of the infrastructure of megacities. Solutions are formed by
logico-analytical processing of data on the situation in general and special cases of
situations for the considered subject of the megalopolis infrastructure. For the prac-
tical implementation of the decision-making mechanism, the article proposes a lin-
guistic-numerical method for determining the potentially best alternative and a fuzzy
situational algorithm for managing the subjects of the megalopolis infrastructure,
based on the structural generality of the situations of a fuzzy situational network.
The obtained results were tested on two real infrastructure subjects of Kyiv.
Keywords: megapolis, infrastructure entities, intelligent decision support system,
linguo-numerical evaluation of alternatives, fuzzy situational algorithm.
INTRODUCTION
From the point of view of the management theory, any megalopolis is a complex
non-stationary spatial system. For objects of this kind, two main features are
characteristic: the dependence of the parameters of the component parts of the
object on their spatial location and the variability of these parameters over time.
The study of such objects with sufficient versatility to obtain practically signifi-
cant results, taking into account the fact that experimental effects on them for
various reasons (limited time frames, the risk of irreversible changes, the high
cost of experiments, etc.) are usually impossible or undesirable. It is possible to
perform almost only by modeling possible situations [1–3]. Especially difficult is
the problem of making effective decisions on the development of the megalopolis
infrastructure, which is associated with large amounts of information, its uncer-
tainty and inconsistency. This problem can solved by using intelligent decision
support systems (IDSS). IDSS is a decision support system with embedded artifi-
cial intelligence techniques exhibiting some or all of the abilities indicative of
intelligent behavior. At the same time, one of the main properties of the intelli-
gence of this system is the ability to generate, analyze, display, search and design
a solution that is not explicit and ready in the system [4–6, 18].
O. Trofymchuk, A. Stenin, M. Soldatova, I. Drozdovich
ISSN 1681–6048 System Research & Information Technologies, 2022, № 2 62
A review of publications on the problems of information IDSS in the field of
infrastructure development of megacities shows that at present the use of intelli-
gent information technologies in this area is mainly limited to the creation of ref-
erence and search engines. Hence, the task of creating fully functional systems
that support all the main stages of decision-making — from the collection and
storage of initial information to the presentation of a reasonable version of the
optimal solution-remains relevant.
STATEMENT OF RESEARCH PROBLEMS
Let be nAAA ,..., 21 — a set of alternatives. Alternatives may or may not specified
at the time of the decision. Let’s also define criteria for evaluating alternatives
nKKK ,..., 21 , which are verbal gradations of quality m
qqq xxX ,...,1 , where is the gra-
dation number ( Nq ,1 ) , m — a set of values of estimates, or otherwise the scale
of the criterion. For discrete scales, the number of gradations is usually small
5,,2m . Discrete scales are ordered in descending order ( 1
qx — best, m
qx —
worst). Utility of the i-th alternative Ai
to the multi-criteria problem denote by.
Sometimes it is allowed that, although in the general case. In addition, introduce
solution classes, defined and ordered by quality (from best to worst). Then, if
ui CAU )( , but vj CAU )( and vu , then )()( ji AUAU , i.e., the utility of
the i-th alternative is higher, since it corresponds to a better class of solutions.
This problem refers to the static problem of determining the optimal solution by
determining the potentially best alternative. In addition to this task, the article
deals with the dynamic problem of determining the potentially best alternative
associated with the operational management of a dynamic object in uncertain
conditions of its operation. The solution of these problems in this article carried
out within the framework of the IDSS of the situational type based on the method
of linguo-numerical estimates and a fuzzy situational control algorithm.
Literature review
When determining the rational solution to a particular problem that arises in the
urban economy, as a rule, it is necessary to take into account a large number of
uncertain and contradictory factors. Uncertainty is an integral part of decision-
making processes for most infrastructure subjects of megapolis [7]. The uncer-
tainty is primarily due to the incompleteness of knowledge about the problem
solved and the inability fully take into account the reaction of the environment,
i.e. the current situation. Inconsistency arises due to ambiguity in the assessment
of situations, errors in the choice of priorities, which, in the end, greatly compli-
cates decision-making. Research shows that decision-makers without additional
analytical support tend to use simplified and sometimes contradictory decision-
making rules. In this case, the most effective tool for making a potentially better
decision is intelligent Decision Support Systems (IDSS). It should note that mod-
ern IDSS is based on the use of specialized information storage (Data Warehouse)
and OLAP (On-Line Analytical Processing) technologies — operational data
analysis. The main purpose of OLAP technologies is dynamic multidimensional
data analysis using an effective Data mining tool, modeling and forecasting [8–10].
Intelligent decision support systems in the development of megalopolis infrastructure
Системні дослідження та інформаційні технології, 2022, № 2 63
It is extremely difficult and almost impossible to reduce tasks with the above
uncertainties by precisely set goals. To do this, you need to “remove” the uncer-
tainty. One of the most common methods of withdrawal is the subjective assess-
ment of a specialist (expert, manager), which determines his preferences. At pre-
sent, the subjective assessment has proved to be the only possible basis for
combining the heterogeneous physical parameters of the problem solved into a
single model that allows evaluating possible solutions. Taking into account the
factor of subjectivity of the decision-maker (LPR) in decision-making violates the
fundamental principle of the methodology of operations research: the search for
an objectively optimal solution. The recognition of the right of the decision-maker
to the subjectivity of the decision is a sign of the emergence of a new paradigm,
characteristic of another scientific direction — decision-making under many crite-
ria. On the other hand, when making decisions on many criteria, there is also an
objective component. Usually, this component includes restrictions imposed by
the external environment on possible solutions (availability of resources, time
constraints, environmental requirements, social situation, etc.) [11, 12].
Decision-making problems usually divided into well structured, weakly
structured and unstructured. The first problem of a substantial relationship be-
tween the main characteristics can expressed quantitatively. Unstructured prob-
lems characterized by the fact that their description dominated by qualitative fac-
tors that are difficult to formalize, and the quantitative relationships between these
factors usually not defined. The intermediate position occupied by weakly struc-
tured problems that combine quantitative and qualitative dependencies, and un-
certainty has a dominant component. Unstructured decision-making problems are
the most complex and characteristic of the infrastructure subjects of megalopolis.
These problems are problems of unique choice in the sense that each time the
problem either new to the decision-maker, or has new features compared to a pre-
viously encountered similar problem [13].
IDSS of situational type
To solve the above problems, the most effective is the situational IDSS, the struc-
ture of which shown in Fig. 1.
Fig. 1. Situational type IDSS structure
O. Trofymchuk, A. Stenin, M. Soldatova, I. Drozdovich
ISSN 1681–6048 System Research & Information Technologies, 2022, № 2 64
In the dialogue with the expert, the situational IDSS provides automated
configuration of the parameters of the subject of the studied megalopolis infra-
structure by entering the basic system of concepts, attributes, values, relations
between them, as well as the types of situations that are typical processes and in-
teractive user interface in the process of its functioning. The model of the process
of functioning of the subject of the megalopolis infrastructure defined as a set of
“regular” situations that represent a fuzzy situational network (FSN) (Fig. 2).
Decisions about the situation formed by logical and analytical processing of
data about the situation in general and special cases of situations for the consid-
ered subject of the megalopolis infrastructure. It assumed that the functioning of
the studied subject of urban infrastructure described on the ‘regular’ situations,
previously synthesized in the subsystem of generation and expert evaluation of
alternatives. Subsystem also identifies for them the potentially best alternatives
(PBA) of rational solutions and control actions.
A ready-made FSN used to determine the sequence of actions or transition
paths between any source and target situation, and this process can fully auto-
mated. An example of a fragment of such a network is shown in Fig. 2, where iS
is the i-th regular situation, iR is the functions that characterize the cost degree
normalized in the range [0,1] during the mutual transition from iS to jS and vice
versa.
To analyze the consequences of the use of certain management alternatives
for current situations, the appropriate scenarios implemented in the subsystem of
modeling and forecasting the development of the situation.
For the selected situation, depending on the goals and conditions of its im-
plementation, the rational control formed in the subsystem for the synthesis of
control actions.
Taking into account the specifics of the infrastructure of megacities in the
ISPR of the situational type in the subsystem of accumulation, storage and updating
R10
R12
R13
R17
R15
R11
R14
R18
R16
s2
R1
R3
R7
R2
R5
s3
R8
R4
R9
s1
s6
s5
s4
s7
s10
s9
s8
s12
s11
Fig. 2. FSN IDSS of situational type
Intelligent decision support systems in the development of megalopolis infrastructure
Системні дослідження та інформаційні технології, 2022, № 2 65
of information, the corresponding requirements for the main structural unit of this
subsystem — the knowledge representation model (KRM) should formulated.
This concerns the system of concepts, the adequacy of the content and correspon-
dence of the formulated knowledge to the studied processes, and the suitability for
performing the required actions. A complete description of the situation does by
the expert, if there is a complete set of indicators that characterize this situation.
To take into account many factors, the original set of indicators can divided into
fragments that combine indicators that form a relatively independent semantic
group. Thus, the task of assessing the situation in the functioning of a megalopolis
subject can divided into a number of specific tasks. The solutions generated by
the particular problems are indicators of a higher degree of generalization, which
serve as the initial data for the particular problems of the next level of the hierar-
chy, etc. This process of decomposition of the overall assessment task leads to the
formation of a multi-level hierarchy of related input-output private tasks. They
solution allows to form a system of solutions for individual aspects and a general
decision on the degree of compliance of the current situation with the goals of the
management in the subject of the megalopolis infrastructure.
Each task (subtask) in the accepted interpretation is a set of functional
dependencies that describe the initial situation and the solution to the situation.
Using the subsystem of logical inference of the generalized assessment of the
situation and the formation of explanations, the rules built and the KRM updated.
The solution of the applied problem carried out by applying the rules from the
KRM database to the data about the current situation.
In other words, when creating an KRM, it is necessary to actually describe
the semantic content of the functioning of the subject of the megalopolis infra-
structure, which guarantees their processing by formal methods. Currently, many
KRM have developed. Having a generic name, they differ in the ideas underlying
them, in terms of mathematical validity.
Obviously, for the above-mentioned situational IDSs, the closest CRM is the
frame model based on the concept of Marvin Minsky. His concept is that the
frame model is a systematized psychological model of a person’s memory and
consciousness. In this sense, it is as close as possible to the creative activity of a
person, including the development of the infrastructure of a megalopolis [14, 15].
For the frame KRM, the data structure is a connected tree structure of nodes
and rules of formalized data accumulated by experts for the subjects of the mega-
lopolis infrastructure. In this case, the linguistic variable ωп of the frame KRM
can described by the following expression:
),,,),(,( MGUnTnn
where )(nT is a term — set of n values that represent the names of fuzzy vari-
ables; U is the domain of definition of each fuzzy variable; G is a syntactic pro-
cedure that serves to expand the set )(nT to generate new elements; M is a spe-
cial semantic procedure for forming a fuzzy set.
Knowledge Z is defined as a tuple of a set of objects Q with a set of im-
plementations of relations F between them and a set of actions N that are per-
formed on elements of Q , i.e.
,,, NFQZ (1)
O. Trofymchuk, A. Stenin, M. Soldatova, I. Drozdovich
ISSN 1681–6048 System Research & Information Technologies, 2022, № 2 66
Production rules can written as sets of fuzzy utterances L
~
:
),THEN)(AND...AND)THEN(IF(
~
11 klaL
where is a generalized linguistic variable defined on the set of input parame-
ters; is a generalized linguistic variable defined on the set of output variables;
k , l is the order of these variables.
For the frame KRM IDSS, the data structure of which is a coherent structure
of formalized data on the subjects of the megalopolis infrastructure, the formation
and selection of a potentially better alternative (rational solution) implemented on
the linguistic-numerical method proposed below.
A linguo-numerical method for determining a potentially better alternative
The main task of the situational type IDSS is to determine the potentially best so-
lution for the current situation, which can be static (for example, choosing the ra-
tional location for the construction of a supermarket) and dynamic (for example,
passenger traffic management). Since alternatives to solutions in this IDSS can
formed both quantitatively and verbally, a linguistic-numerical method for deter-
mining the potentially best alternative (PBA) proposed. The following is an ex-
ample of a linguistic rating scale:
very low → 2, low → 3, average → 4, high → 5, very high.
To date, there is a large selection of methods for evaluating the generated set
of alternatives and selecting the best alternatives [11, 13]. These decision-making
methods for evaluating and selecting potentially better alternatives are effective
with a small power of the set of evaluated alternatives (no more than 5–10). To
evaluate the set of high-power alternatives, which corresponds to the above-
mentioned tasks of managing the subjects of the megalopolis infrastructure, it
proposed to use intelligent methods, in particular, fuzzy logic methods, which
allow for automatic ranking of alternatives based on decision rules.
To enable the evaluation of alternatives based on linguistic variables, the
scheme of the fuzzy inference procedure is used (Fig. 3) [16].
Since in the KRM, the reason corresponds to the KRM frame, which con-
tains a ready-made mechanism for implementing this reason (sub-goal), the pro-
cedure for general fuzzy inference is greatly simplified. In addition, since the pa-
rameters that can qualitatively evaluated by the studied subject of the city
infrastructure have a different physical nature, the natural requirement for its ob-
jective assessment is the introduction of a single normalized rating scale in a cer-
tain range at the fuzzification stage.
Fig. 3. The scheme of the fuzzy inference procedure
Intelligent decision support systems in the development of megalopolis infrastructure
Системні дослідження та інформаційні технології, 2022, № 2 67
Let the attributes that form the alternatives iA contain both numerical (quan-
titative) and linguistic variables (qualitative). In this case, each variable is as-
signed a belonging function. In this case, we will use the universal scale ]1,0[ to
evaluate preferences. In other words, for the set ]1,0[x and the membership
function : ]1,0[x , the fuzzy set is defined as
}))(,{(
~
XxxxA A . (2)
The belonging function (1) quantifies the membership of the elements of the
set of alternatives A , defined by Ax to the fuzzy set A
~
, with normalized vari-
ables x~ A value of 0 means that the element does not include a fuzzy set, and 1
means that the element is completely described by this set. Among the most well-
known and used belonging functions, the most convenient and universal for the
variables under consideration are linear and trapezoidal functions of the form
[6, 7, 18]:
The graphs of the belonging functions correspond to the ascending (Fig. 4, a)
and descending (Fig. 4, b) preference scales, respectively. Thus, for all quantita-
tive evaluations of max and min values of the variable ija and ijb are known, and
for all linguistic (verbal) ratings, they are determined by the maximum and mini-
mum number of linguistic scale (see example linguistic scale).
The potentially best alternative determined by the formula
),...,2,1(max
~
1
mjxJA
n
i
ijiiopt
, (3)
where ijx~ — I variable of the j alternative.
The practical use of this method has shown the identity of its results to the
well-known methods PARK, ORKLASS, QUERY, CORD, etc. [13], but the
complexity of the decision-making process of the proposed method is signifi-
cantly lower. This is due to the lack of a procedure for pairwise comparison of the
selected parameters of the studied subject of the megalopolis infrastructure. The
most effective application of this approach to the assessment and selection of the
PBA of the studied subject of the megalopolis infrastructure is expedient with a
large number of characteristic parameters of this subject.
1
0
1
0
μ(xij)
μ(xij)
xij xij aij aijbij bija b
Fig. 4. Graphs of belonging functions
O. Trofymchuk, A. Stenin, M. Soldatova, I. Drozdovich
ISSN 1681–6048 System Research & Information Technologies, 2022, № 2 68
Fuzzy situational control subjects of infrastructure of the megapolis
Let the current situation of a megalopolis infrastructure subject described as
a fuzzy situation of the following type:
XxxxMS iiisTEK i
},/)({ , (4)
where the function of belonging to a linguistic variable ix , describing the current
situation.
Since each linguistic variable corresponds to the j-th term from the set of
terms of KRM, the formula (4) can written as:
,;,1;,1},/)({
)(
XxNiMjTTMS i
i
j
i
jMi ixis
where j-th term i-th linguistic variable.
To determine the control action for the current state you want to compare
this situation fuzzy fuzzy with each situation from a set of existing KRM in the
test subject of city’s infrastructure “regular” situations, which on the basis of ex-
pert methods elaborated by standard control actions.
From the point of view, the most convenient measure of proximity can con-
sidered the degree of fuzzy inclusion of the situation, which characterized by a
certain inclusion threshold determined by the developer, based on the conditions
in which the subject of the megalopolis infrastructure operates. The inclusion
threshold defined, as well as the belonging functions, in the normalized range
[0, 1] as follows:
,]1,[ mininclt
where the lower limit of the range of the degree of inclusion, usually. In this case,
we can talk about how fuzzy the signs of the current STEK situation are indis-
tinctly included in the fuzzy values of the corresponding signs of the situation [2,
6].
If a “regular” situation found that is sufficiently close to this current one,
then from the set of alternatives for this “regular” situation, the PBA for which the
control action implemented selected. If such proximity not found, then the current
situation processed in the subsystem for generating and expert evaluation of alter-
natives, after which its dynamic assessment is carried out for the found PBA in
the subsystem for modeling and predicting the development of the situation. Fur-
ther, in the subsystem of synthesis of control actions, the corresponding control
formed. This situation then transferred to the category of “regular”. The algorithm
for implementing fuzzy situational control based on IDSS shown by the dotted
arrows in Fig. 1.
In addition, if the external working conditions of the studied subject of the
megalopolis infrastructure change, it becomes necessary to move from one “regu-
lar” situation to another. The possible transition from one “regular” situation to
another carried out with the help of some strategy.
The strategy is described by the optimal FSN route between the current
fuzzy situation Ssi and the target situation Ssc . Transitions are determined
by iR solutions, which correspond to a certain degree of cost. The total number of
situations and transitions between them in the FSN describing the real subjects of
Intelligent decision support systems in the development of megalopolis infrastructure
Системні дослідження та інформаційні технології, 2022, № 2 69
the megalopolis infrastructure can be very large. To simplify the search task,
management strategies use various optimization methods (for example, the dy-
namic programming method).
Given that the subjects of the megalopolis infrastructure in most cases have
mutual independence of the values of the features, it proposed to use the FSN
compression method based on the definition of “community structures”. Commu-
nity structures Oi that have non-empty intersections with each other called
neighbors, and the set of vertices of the intersection area of two neighboring
structures called the transition area of community structures. For the fragment of
the FSN (Fig. 2), the structures of generality of situations with the costs of mutual
transitions have the form shown in Fig. 5.
The essence of the proposed approach based on the NSS compression
method for the given NSS fragment is as follows. As an optimality criterion in the
conditional example, we use use the minimum of total costs. The path that has the
minimum cost considered optimal. Let’s determine the optimal transition from 2s
to 9s . Given that 92 OO Ø (empty set), it is not possible to go from 2s to 9s
using a single local control solution. Since there are no pairs of vertices adjacent
to each other from the number belonging to 2O and 9O , we proceed to find the
shortest possible path between all pairs of vertices of the sets 2O and 9O . The
shortest path ),,,( 7632 OOOOL . Moving to the transition points of neighboring
structures of the common path L, we get the control strategy:
),,,,(),( 9854292 sssssssC . The desired path in Fig. 2 highlighted with a dotted
line.
O1
O2
O4
O7
O5
O6
O8
O9
O3
s1
s2
s4
s3
s6
s5
s12
s7
s8
s10 s
s9
Fig. 5. Community structures of FSN IDSS
O. Trofymchuk, A. Stenin, M. Soldatova, I. Drozdovich
ISSN 1681–6048 System Research & Information Technologies, 2022, № 2 70
Practical implementation of the results obtained
The researches in the article was carried out within the framework of research
work “Research of methods and tools for creating a hybrid computing technology
for constructing a quasi-formalized forecasting model in conditions of data het-
erogeneity and non-normative deviations in organizational management systems”
(S/R 0117U002448). The obtained results tested on two real subjects of the infra-
structure of Kiev.
Construction of social objects. Assessed the appropriateness of the choice
of the construction site of a supermarket. The expert group suggested the follow-
ing criteria: price, population density within a radius of 1 km, the presence of
competitors, infrastructure connections, the number of places for car Parking, ac-
cess places through public transport and the visibility of the supermarket from the
nearby major streets, as well as data on these criteria. Four possible supermarket
construction sites were evaluated (alternatives var. 1 — var. 4). In one of them, a
supermarket built in Kiev. Expert assessments listed in Table 1.
T a b l e 1 . Initial expert assessments
Alternatives
ijx Variables
var. 1 var. 2 var. 3 var. 4
jx1 The number of places
for car Parking, max 400 300 250 150
jx2 Presence of the competitors, min 1 (few) 5 (many) 3 (average) 5 (many)
jx3 Population density in 1 km radius, max 200 4500 6000 7000
jx4
The cost of the placement, million
UAH, min 6 16 12 20
jx5 The flow of public transport, max 1 (low) 3 (average) 5 (high) 7 (very
high)
jx6
Main street visibility, max 5 (good) 5 (good) 3 (average) 1 (bad)
jx7
Infrastructure, max 3
(average) 3 (average) 5 (good) 7 (very
good)
After the procedure of fuzzification and normalization of linguistic variables
according to the formula (2) and Fig. 4, a) and Fig. 4, b), we summarize their val-
ues in Table 2.
T a b l e 2 . Sum of data
Alternatives
Variables
var. 1 var. 2 var. 3 var. 4
jx1
~
1 0,6 0,4 0,0
jx2
~
1 0,33 0,66 0,33
jx3
~
0 0,63 0,85 1
jx4
~
1 0,285 0,57 0
jx5
~
0 0,33 0,66 1
jx6
~ 0,66 0,66 0,33 0
jx7
~ 0,33 0,33 0,66 1
7
1i ijx 3,99 3,165 4,13 3,33
Intelligent decision support systems in the development of megalopolis infrastructure
Системні дослідження та інформаційні технології, 2022, № 2 71
Then, using the formula (3), we obtain the following estimates of alternative
options: 3,99; 3,165; 4,13; 3,33, from which it follows that the potentially best
alternative (PBA) is the alternative var. 3, which confirmed the feasibility of this
supermarket construction site. It should note that the alternative var.1 is also of
interest to the decision-maker.
Public transport. Today, the development and effective management of
transport is unthinkable without the development and application of intelligent
control systems. The process of transportation of passengers by urban passenger
transport based on the observance of the schedule of movement of vehicles along
the route in accordance with the pre-established schedule of movement. In most
motor transport companies of Ukraine, the management of the passenger transpor-
tation process controlled by the dispatcher for compliance with the traffic sched-
ule.
Due to the transience of changing road situations, the lack of complete in-
formation about the situation on the route, the presence of many uncertainties
when receiving it, it is impossible to build a reliable forecast of the development
of the situation over a long time interval. Thus, the decision-making by the
dispatcher takes place in a difficult situation and requires a lot of psycho-
physiological stress from the dispatcher [17, 8].
To assess the effectiveness and sustainability of the decisions made by the
dispatcher in the process of managing the movement of public transport, one of
the bus routes in Kiev selected for the study. The scheme of implementation of
control solutions for fuzzy situational management of public transport traffic
shown in Fig. 6. The use of a fuzzy situational algorithm for controlling the
movement of urban transport for 3 weeks made it possible to increase the effi-
ciency of transport on this route (Fig. 7, red line). In addition, the dispatcher with
the help of the ISPR could quickly make operational decisions on the “emer-
gency” situations that arose, which reduced the economic losses of the transport
company.
Fig. 6. Fuzzy situational control
O. Trofymchuk, A. Stenin, M. Soldatova, I. Drozdovich
ISSN 1681–6048 System Research & Information Technologies, 2022, № 2 72
The article proposes an intelligent decision support system, the main ele-
ments of which are a fuzzy situational network and a frame model for represent-
ing the knowledge of the subjects of the megalopolis infrastructure. This allows
us to formalize the “regular” situations that arise in the course of the activities of
the subjects of the megalopolis infrastructure using the theory of fuzzy sets, and
then determine the optimal control actions for them. If it is necessary to move
from one “regular” situation to another with minimal costs, an algorithm based on
the structural generality of situations is used. When an “unregular” current situa-
tion occurs, its maximum proximity to one of the “regular” situations determined
and linguo-numerical alternatives to decision-making generated. The selection of
the potentially best ones based on a logical inference scheme. After that, the op-
timal control action for this current situation synthesized and identified in the
knowledge representation model as “regular”.
CONCLUSION
The article proposes an intelligent decision support system, the main elements of
which are a fuzzy situational network and a frame model for representing the
knowledge of the subjects of the megalopolis infrastructure. This allows us to
formalize the “regular” situations that arise in the course of the activities of the
subjects of the megalopolis infrastructure using the theory of fuzzy sets, and then
determine the optimal control actions for them. If it is necessary to move from
one “regular” situation to another with minimal costs, an algorithm based on the
structural generality of situations is used. When an “unregular” current situation
occurs, its maximum proximity to one of the “regular” situations determined and
linguo-numerical alternatives to decision-making generated. The selection of the
potentially best ones based on a logical inference scheme. After that, the optimal
control action for this current situation synthesized and identified in the knowl-
edge representation model as “regular”.
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Intelligent decision support systems in the development of megalopolis infrastructure
Системні дослідження та інформаційні технології, 2022, № 2 73
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Received 10.01.2022
O. Trofymchuk, A. Stenin, M. Soldatova, I. Drozdovich
ISSN 1681–6048 System Research & Information Technologies, 2022, № 2 74
INFORMATION ON THE ARTICLE
Oleksandr M. Trofymchuk, ORCID: 0000-0003-3358-6274, Institute of
telecommunications and global information space of NAS of Ukraine, Ukraine, e-mail:
itc_nasu@ukr.net
Aleksandr A. Stenin, ORCID: 0000-0001-5836-9300, National Technical University
of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine, e-mail:
alexander.stenin@yandex.ua
Maria A. Soldatova, ORCID: 0000-0003-1233-1272, National Technical University of
Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine, e-mail:
benten1093@gmail.com
Irina G. Drozdovich, ORCID: 0000-0002-4216-2417, Institute of telecommunications
and global information space of NAS of Ukraine, Ukraine, e-mail:
irinashitikova54@gmail.com
ІНТЕЛЕКТУАЛЬНІ СИСТЕМИ ПІДТРИМАННЯ ПРИЙНЯТТЯ РІШЕНЬ
У РОЗВИТКУ ІНФРАСТРУКТУРИ МЕГАПОЛІСУ / О.М. Трофимчук,
О.А. Стенін, А.О. Солдатова, І.Г. Дроздович
Анотація. Мегаполіс з точки зору теорії управління являє собою складну не-
стаціонарну просторову систему. Проблему прийняття інноваційних рішень
щодо розвитку їх інфраструктури зумовлено наявністю великого обсягу інфор-
мації, її невизначеністю і суперечливістю. У роботі розглянуто принципи по-
будови інтелектуальних систем підтримання прийняття рішень ситуаційного
типу для інноваційного розвитку інфраструктури мегаполісів. Рішення фор-
муються шляхом логіко-аналітичного оброблення даних про ситуацію в ціло-
му і окремих випадках ситуацій для розглянутого суб’єкта інфраструктури ме-
гаполісу. Для практичної реалізації механізму прийняття рішень
запропоновано лінгвочисловий метод визначення потенційно кращої альтерна-
тиви та нечіткий ситуаційний алгоритм управління суб’єктами інфраструктури
мегаполісу, заснований на структурній спільності ситуацій нечіткої ситуацій-
ної мережі. Отримані результати протестовано на двох реальних об’єктах ін-
фраструктури Києва.
Ключові слова: мегаполіс, інфраструктурні об’єкти, інтелектуальна система
підтримання прийняття рішень, лінгво-числове оцінювання альтернатив, нечі-
ткий ситуаційний алгоритм.
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| id | journaliasakpiua-article-265576 |
| institution | System research and information technologies |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2025-07-17T10:27:57Z |
| publishDate | 2022 |
| publisher | The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" |
| record_format | ojs |
| resource_txt_mv | journaliasakpiua/34/d59f8f69562c60ad7f49493b1960a834.pdf |
| spelling | journaliasakpiua-article-2655762022-10-17T22:12:39Z Intelligent decision support systems in the development of megalopolis infrastructure Інтелектуальні системи підтримання прийняття рішень у розвитку інфраструктури мегаполісу Trofymchuk, Oleksandr Stenin, Aleksandr Soldatova, Maria Drozdovich, Irina мегаполіс інфраструктурні об’єкти інтелектуальна система підтримання прийняття рішень лінгво-числове оцінювання альтернатив нечіткий ситуаційний алгоритм megapolis infrastructure entities intelligent decision support system linguo-numerical evaluation of alternatives fuzzy situational algorithm From the point of view of the management theory, a megapolis is a complex non-stationary spatial system. The problem of making innovative decisions on the development of their infrastructure is caused by the presence of a large amount of information, its uncertainty and inconsistency. This article discusses the principles of building intelligent decision support systems of a situational type for the innovative development of the infrastructure of megacities. Solutions are formed by logico-analytical processing of data on the situation in general and special cases of situations for the considered subject of the megalopolis infrastructure. For the practical implementation of the decision-making mechanism, the article proposes a linguistic-numerical method for determining the potentially best alternative and a fuzzy situational algorithm for managing the subjects of the megalopolis infrastructure, based on the structural generality of the situations of a fuzzy situational network. The obtained results were tested on two real infrastructure subjects of Kyiv. Мегаполіс з точки зору теорії управління являє собою складну нестаціонарну просторову систему. Проблему прийняття інноваційних рішень щодо розвитку їх інфраструктури зумовлено наявністю великого обсягу інформації, її невизначеністю і суперечливістю. У роботі розглянуто принципи побудови інтелектуальних систем підтримання прийняття рішень ситуаційного типу для інноваційного розвитку інфраструктури мегаполісів. Рішення формуються шляхом логіко-аналітичного оброблення даних про ситуацію в цілому і окремих випадках ситуацій для розглянутого суб’єкта інфраструктури мегаполісу. Для практичної реалізації механізму прийняття рішень запропоновано лінгвочисловий метод визначення потенційно кращої альтернативи та нечіткий ситуаційний алгоритм управління суб’єктами інфраструктури мегаполісу, заснований на структурній спільності ситуацій нечіткої ситуаційної мережі. Отримані результати протестовано на двох реальних об’єктах інфраструктури Києва. The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2022-08-30 Article Article application/pdf https://journal.iasa.kpi.ua/article/view/265576 10.20535/SRIT.2308-8893.2022.2.04 System research and information technologies; No. 2 (2022); 61-74 Системные исследования и информационные технологии; № 2 (2022); 61-74 Системні дослідження та інформаційні технології; № 2 (2022); 61-74 2308-8893 1681-6048 en https://journal.iasa.kpi.ua/article/view/265576/261623 |
| spellingShingle | мегаполіс інфраструктурні об’єкти інтелектуальна система підтримання прийняття рішень лінгво-числове оцінювання альтернатив нечіткий ситуаційний алгоритм Trofymchuk, Oleksandr Stenin, Aleksandr Soldatova, Maria Drozdovich, Irina Інтелектуальні системи підтримання прийняття рішень у розвитку інфраструктури мегаполісу |
| title | Інтелектуальні системи підтримання прийняття рішень у розвитку інфраструктури мегаполісу |
| title_alt | Intelligent decision support systems in the development of megalopolis infrastructure |
| title_full | Інтелектуальні системи підтримання прийняття рішень у розвитку інфраструктури мегаполісу |
| title_fullStr | Інтелектуальні системи підтримання прийняття рішень у розвитку інфраструктури мегаполісу |
| title_full_unstemmed | Інтелектуальні системи підтримання прийняття рішень у розвитку інфраструктури мегаполісу |
| title_short | Інтелектуальні системи підтримання прийняття рішень у розвитку інфраструктури мегаполісу |
| title_sort | інтелектуальні системи підтримання прийняття рішень у розвитку інфраструктури мегаполісу |
| topic | мегаполіс інфраструктурні об’єкти інтелектуальна система підтримання прийняття рішень лінгво-числове оцінювання альтернатив нечіткий ситуаційний алгоритм |
| topic_facet | мегаполіс інфраструктурні об’єкти інтелектуальна система підтримання прийняття рішень лінгво-числове оцінювання альтернатив нечіткий ситуаційний алгоритм megapolis infrastructure entities intelligent decision support system linguo-numerical evaluation of alternatives fuzzy situational algorithm |
| url | https://journal.iasa.kpi.ua/article/view/265576 |
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