Vestnik of Ryazan State
Radio Engineering University

UDC 621. 387.322

K. I. Nikishin, Ph.D. (Tech.), senior lecturer, department of computer science, PSU, Penza, Russia;
orcid.org/0000-0001-7966-7833, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

In the modern world among all network technologies the wireless technologies occupy a special place.
We have the necessity to develop and implement new algorithms and protocols in wireless technologies. The
main and most perspective direction in wireless systems is the design of systems for monitoring and control
of object parameters. Special place in this direction is occupied by wireless sensor networks (WSN). The aim
of the research is to study the protocols of wireless sensor networks and their synchronization algorithms
using modern modeling environment OMNET++. The main tasks of the research are to study WSN standards,
WSN protocol such as IEEE 802.15.4 WPAN and its modeling with efficiency assessment. The developed
model made it possible to verify algorithms and evaluate the performance of network nodes, network
bandwidth and efficient power consumption.

Key words: wireless technologies, wireless sensor networks, self-organizing networks, IEEE 802.15.4

WPAN protocol, coordinator, modeling, OMNET++, Castalia.

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UDC 004.021

RESEARCH AND ANALYSIS OF TRANSPORT PROBLEMS

IN URBAN ENVIRONMENTS

A. S. Alyoshkin, Ph.D. (Tech.), associate professor, MIREA, Moscow, Russia;
orcid.org/0000-0003-2190-700X, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

This article considers the approaches for the tasks of traffic situation forecasting and building op-timal
planning systems. The aim is to study and analyze problems in the field of traffic automation, carried out
through a review of foreign sources devoted to the tasks and algorithms of this subject ar-ea. Various topics
and approaches selection in a given area is carried out. A translation is provided-as a presentation of foreign
sources. Common approaches and problems when solving the tasks of forecasting road situation are
given.

Key words: road traffic forecasting, radial basis function network, RBFNN, particle swarm optimization,

PSO, intelligent transportation systems, ITS, line planning.

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UDC 004.62

THE METHOD TO COMPRESS IN INTERMEDIATE DATA

IN DISTRIBUTED MINING OF ASSOCIATION RULES

E. O. Khramshina, postgraduate student, lecturer assistant of the Department of Computational and Applied
Mathematics, RSREU, Ryazan, Russia;
orcid 0000-0002-4490-8403, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

The aim of this work is to decrease memory volume for storage and transfer taken by three-dimensional
array in distributed mining of association rules. Volume decrease is achieved due to sparse array and variable
size of array element values. Array elements with non-zero values are written as a number pair: the offset
from the previous element with non-zero value and the value itself. To separate numbers, one of the bits in a
byte is used as a service one, to point the end of the value. The experiments have shown that this method allows
file size 74% less on average in comparison with the original array. Software in Java programming
language has been developed for these experiments. The compression method together with 3D2ARM association
rules algorithm can be used to develop distributed mining of association rules.

Key words: data mining, association rules mining, 3D2ARM algorithm, data structures, data transfer,

data compression, zero-length suppression method, variable size of array values.

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UDC 519.766.2

RAPID CALCULATION OF CONSEQUENTS FUZZINESS
INDICES AFTER MAMDANI IMPLICATION
AND FURTHER AGGREGATION

K. V. Bukhensky, Ph.D. (Phys. and Math.), associate professor, Head of the Department of Higher
Mathematics, RSREU, Ryazan, Russia;
orcid.org/0000-0003-2602-2112, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
A. N. Konyukhov, Ph.D. (Ped.), associate professor, RSREU, Ryazan, Russia;
orcid.org/0000-0002-1523-7110, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
K. V. Anisimov, fourth year student of the Faculty of Computer Science, RSREU, Ryazan, Russia;
orcid.org/0000-0001-8889-0818, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

The aim is to – 1) obtain the analytical formula for consequent index of fuzziness after Mamdani implication
(rule); 2) derive the analytical formula for fuzziness index of a fuzzy set (FS) gained after aggregation
of arbitrary number subnormal consequents of Mamdani implication. This work is the proceeding of former
research on the project “Fuzziness transformations in fuzzy inference systems (FIS)”. As a measure of math
fuzziness a Yager’s index with linear Hamming metric was used. The analytical formulas for integral functions
of fuzziness index for some shape functions (IFFI SF) of LR-types of fuzzy numbers (FNs) were derived.
IFFI SF allows us to calculate FS’s index of fuzziness obtained from FNs via logical operations. Common
and partial formulas for LR-type FNs with linear and clipped parabola shape functions were represented. In
order to test theoretical results several numerical experiments were accomplished. The expressions obtained
allow calculating the index of fuzziness for FSs after Mamdani implication and further consequents aggregation
without integration procedure thus reducing calculation time dramatically. Formulas may be further
analyzed in order to search the optimal conditions of Mamdani type inference in the terms of fuzziness.

Key words:fuzzy set, LR-type fuzzy number, membership function, shape function, index of fuzziness, integral

functions of fuzziness index, antecedent, consequent, Mamdani implication, linguistic variable term,
cross-factor.

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