ISSN 1991-2927
 

ACP № 2 (56) 2019

Author: "Valeriia Vadimovna Voronina"

Valeriia Vadimovna Voronina, Ulyanovsk State Technical University, Candidate of Engineering; graduated from the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University; Associate Professor at the Department of Information Systems of Ulyanovsk State Technical University; an author of articles in the field of intellectual analysis of time series. [e-mail: vvsh85@mail.ru]V. Voronina,

Sergei Orestovich Smerechinskii, “AIS Gorod” Company, Magister; finished his Master’s studies at the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University; Software Engineer at “AIS Gorod” Company; an author of articles in the field of software development. [e-mail: quigon173@gmail.com]S. Smerechinskii

The System for Modelling the Cluster Simulating Processes of Big Data Analysis 000_9.pdf

The subject area for processing Big Data with the use of cluster systems is described in the article. The paper examines the existing methods of processing Big Data on which the proposed solution for increasing the efficiency of the cluster functioning is based. As basic solutions for building and proposing ways to increase the efficiency of the cluster, the Hadoop technology and the MapReduce methodology were chosen. The efficiency of cluster systems involves consideration of cluster processes in the form of the hierarchical architecture consisting of three levels: cluster node level, cluster segment level and cluster topology level. The paper indicates solutions that can be useful in order to improve the efficiency of cluster resource allocation by choosing the topology of cluster construction, using the more efficient load-balancing algorithm, and using graphics processors, which involves distributing computational loads between CPU and GPU. Recommendations proposed in the article are verified experimentally.

Big data, cpu, gpu, mapreduce, big data, cluster, balancing algorithm, topology, cpu, gpu, mapreduce.

2017_ 3

Sections: Information systems

Subjects: Information systems, Automated control systems.


Nadezhda Glebovna Yarushkina, Ulyanovsk State Technical University, Doctor of Engineering, Professor, First Vice-Rector - Vice-Rector for Science of Ulyanovsk State Technical University (UlSTU); graduated from the Faculty of Radioengineering of Ulyanovsk State Technical University; an author of more than 250 papers in the field of soft computing, fuzzy logic, and hybrid systems. [e-mail: jng@ulstu.ru]N. Yarushkina,

Valeriia Vadimovna Voronina, Ulyanovsk State Technical University, Candidate of Engineering; graduated from the Faculty of Information Systems and Technologies at Ulyanovsk State Technical University; Associate Professor at the Department of Information Systems at Ulyanovsk State Technical University; an author of articles in the field of intellectual analysis of time series. [e-mail: vvsh85@mail.ru]V. Voronina,

Irina Aleksandrovna Timina, Ulyanovsk State Technical University, Assistant at the Department of Information Systems at Ulyanovsk State Technical University; graduated from the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University with a specialty of Applied Informatics (in Economics); an author of articles in the field of intellectual analysis of time series. [e-mail: timina_i@mail.ru@ulstu.ru]I. Timina,

Evgenii Nikolaevich Egov, Ulyanovsk State Technical University, Assistant at the Department of Information Systems at Ulyanovsk State Technical University; graduated from the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University; an author of articles in the field of intellectual analysis of time series. [e-mail: e.egov@ulstu.ru]E. Egov

Forecasting Technical System State With the Application of Entropy Measure for Fuzzy Time Series Diagnosis 000_6.pdf

This article discusses the ways to forecast time series of technical systems on the basis of the hypothesis of trends conservation, the hypothesis of trends stability and the hypothesis of forecasting for a specified period as well as forecasting with the use of the measure of entropy for fuzzy time series. The method of calculating the measure of entropy for fuzzy time series has been described in the previous issue of the journal. The software system of diagnosing and forecasting fuzzy time series based on the measure of entropy is also considered in the article. The system is divided into several modules, with the opportunity to use some of them in the other systems of time series prediction. The main interest of this paper is the prediction algorithm that was designed on the basis of time series measure of entropy and the comparison of the two approaches to forecasting fuzzy time series. The comparison was made on the basis of the values of MAPE, MSE, RMSE errors obtained from values of 10 rows predicted by two programs. The first program is based on the selection of one of the hypotheses, the second one described in this article is based on the prediction with the use of measure of entropy. This article is intended for professionals diagnosing technical systems.

Measure of entropy, prediction, time series.

2015_ 3

Sections: Mathematical modeling

Subjects: Mathematical modeling, Automated control systems.


Valeriia Vadimovna Voronina, Ulyanovsk State Technical University, Candidate of Engineering, Associate Professor at the Department of Information Systems of Ulyanovsk State Technical University; graduated from the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University; an author of articles in the field of intellectual analysis of time series. [e-mail: vvsh85@mail.ru]V. Voronina,

Albert Damirovich Mukhametzianov, Ulyanovsk State Technical University, Candidate for the Master’s Degree; graduated from the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University and got the Bachelor’s Degree in 2015; an author of articles in the field of intelligent system development. [e-mail: desperado@x-cart.com]A. Mukhametzianov,

Iuliia Sergeevna Baldina, Ulyanovsk State Technical University, Candidate for the Master’s Degree; graduated from the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University and got the Bachelor’s Degree in 2015; an author of articles in the field of intelligent system development. [e-mail: uliya.baldina@gmail.com]I. Baldina

Development of Web-service for Operation With Programmable Logic Devices 000_13.pdf

The current information system is an integral resource for full-fledged operation with programmable logic devices (PLD) and with the functions of remote programming, knowledge storage and experience exchange of the particular field between developers. The result of the system operation is the model of fuzzy controller that represents an intelligent automated control system (ISAU) in a small way with the ability of adaption to changing conditions of operation (due to the fuzzy controller implemented through a fuzzy algorithm on pseudo-fuzzy language). The goal of the project is to provide the convenient integrated programming environment with the good condition for education. The article considers the description and the way of implementation of the project architecture; diagrams and stages of resulting fuzzy controller design process and the description of the developed decision support system for choosing PLD are shown

Cloud service, programmable logic device (pld), intelligent automated control system.

2015_ 3

Sections: Electronic and electrical engineering

Subjects: Electrical engineering and electronics, Automated control systems.


Nadezhda Glebovna Yarushkina, Ulyanovsk State Technical University, Doctor of Engineering, Professor, First Vice-Rector - Vice-Rector for Science of Ulyanovsk State Technical University; graduated from the Faculty of Radioengineering of Ulyanovsk State Technical University ; an author of more than 250 papers in the field of soft computing, fuzzy logic, and hybrid systems. [e-mail: jng@ulstu.ru]N. Yarushkina,

Valeriia Vadimovna Voronina, Ulyanovsk State Technical University, Candidate of Engineering, Associate Professor at the Department of Information Systems at Ulyanovsk State Technical University; graduated from the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University; an author of articles in the field of intellectual analysis of time series [e-mail: vvsh85@mail.ru]V. Voronina,

Evgenii Nilolaevich Egov, Ulyanovsk State Technical University, Assistant at the Department of Information Systems at Ulyanovsk State Technical University; graduated from the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University; an author of articles in the field of intelligent information systems. [e-mail: e.egov@ulstu.ru]E. Egov

Entropy Application to the Diagnosis of Technical Time Series 000_6.pdf

The article deals with the method for time series diagnosis based on the measure of the time series uncertainty. The formula for finding the measure of entropy for fuzzy time series is determined. The algorithm for finding the measure of entropy for fuzzy time series is of particular interest. A model of expert diagnostic rules for aircraft accessories is developed. The models of the behavior of objects such as the main gearbox and power plant engine helicopter are offered. Interpretation of natural experiment for the purpose of diagnosis of helicopter units held by analyzing the quality of the built models. A set of programs for mathematical modeling and predicting the behavior of aircraft accessories based on fuzzy measure of the uncertainty of the time series is developed. The model showed high accuracy in determining the characteristics of the time series and the identification of dangerous areas while experimenting. The developed algorithm can be successfully applied for the diagnosis and prediction of time series. This article is intended for specialists diagnosing technical systems.

Measure of entropy, diagnosis, time series.

2015_ 2

Sections: Information systems

Subjects: Information systems.


Nadezhda Glebovna Yarushkina, Ulyanovsk State Technical University, Doctor of Engineering, Professor; Pro-Rector for Science; head of the Chair 'Information Systems' at Ulyanovsk State Technical University; author of articles and monographs in the field of intellectual analysis of data. [e-mail: jng@ulstu.ru]N. Yarushkina,

Valeria Vadimovna Voronina, Ulyanovsk State Technical University, Post-graduate student at the Chair 'Information Systems' of Ulyanovsk State Technical University; graduated from the Faculty of Information Systems and Technology of Ulyanovsk State Technical University; author of articles in the field of intellectual systems for storage and processing of data. [e-mail: vvsh85@mail.ru]V. Voronina,

Tatiana Vasilyevna Afanasyeva, Ulyanovsk State Technical University, Candidate of Engineering, Associate Professor at the Chair 'Applied Mathematics and Information Science' of Ulyanovsk State Technical University; author of articles, a monograph in the field of intellectual analysis of data. [e-mail: tv.afanaseva@mail.ru]T. Afanasyeva

Diagnostics of Helicopter Nodes on Basis of a Model of Grained Time Series 26_8.pdf

In the present paper the authors consider a solution to the problem of diagnostics of helicopter nodes. The diagnostics is carried out by analyzing time series of key physical quantities, based on an expert rulebase containing statements on the significance of trends of change of these variables. In the paper, some expert rules for the helicopter nodes such as a helicopter propulsion engine and main gearbox, are also folmulated.

Diagnostics, time series, helicopters, expert rulebase.

2011_ 4

Sections: Artificial-intelligence systems

Subjects: Artificial intelligence, Information systems.


Nadezhda Glebovna Yarushkina, [e-mail: mars@mv.ru]N. Yaroushkina,

Irina Grigorievna Perfilyeva, [e-mail: mars@mv.ru] I. Perfilyeva,

Andrey Gennadievich Igonin, [e-mail: mars@mv.ru] A. Igonin,

Anton Alexeevich Romanov, [e-mail: mars@mv.ru] A. Romanov,

Tagir Ragatovich Younusov, [e-mail: mars@mv.ru] T. Yunusov,

Valeriia Vadimovna Shishkina, [e-mail: mars@mv.ru] V. Shishkina

Development of Internet-service Integrating Fuzzy Modeling and Analysis of Fuzzy Tendencies of Time Series 20_10.pdf

The article presents an implementation of a new service-oriented architecture of a new fuzzy-modeling method. The novelty of the got software in the form of Internet-service consists in the implementation of a new integral method of fuzzy modeling and analysis of fuzzy tendencies of time series in order to increase management-decision efficiency as well as in the accounting of new management requirements for reduction of costs concerning maintenance, operation and update/upgrade of software and hardware. The integral-method analysis results in the fact that the error of short-term forecast precision does not exceed 20%, the errors of short-term forecast of fuzzy-tendency types are equal to 0.

Intellectual system, decision-making, internet-service, fuzzy modeling, forecast of time series.

2010_ 2

Sections: Theoretical issues of automation of command and control processes

Subjects: Artificial intelligence.


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