ISSN 1991-2927
 

ACP № 3 (61) 2020

Author: "Irina Aleksandrovna Timina"

Vadim Sergeevich Moshkin, Ulyanovsk State Technical University, Assistant of 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 more than 40 papers in the field of intelligent systems. [e-mail: postforvadim@yandex.ru]V. Moshkin,

Aleksandr Nikolaevich Pirogov, JSC ‘Aviastar-SP’, Postgraduate Student of the Institute of Aviation Technologies and Managements of Ulyanovsk State Technical University, Head of the Department of Invest Projects at JSC ‘Aviastar-SP’. [e-mail: anpirogov@icloud.com]A. Pirogov,

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 intelligent analysis of time series. [e-mail: timina_i@mail.ru@ulstu.ru]I. Timina,

Vadim Viktorinovich Shishkin, Institute of Aviation Technology and Managements of Ulyanovsk State Technical University, Candidate of Engineering, Associate Professor; graduated from the Faculty of Radioengineering of Ulyanovsk Polytechnic Institute; Head of the Institute of Aviation Technology and Managements of Ulyanovsk State Technical University, an author of articles in the field of automated design of industrial products and Data Mining. [e-mail: shvv@ulstu.ru]V. Shishkin,

Nadezhda Glebovna Yarushkina, Ulyanovsk State Technical University, Doctor of Engineering, Professor; graduated from the Faculty of Radioengineering at Ulyanovsk State Technical University; First Vice-Rector - Vice-Rector for Scientific Affairs 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

Intelligent Analysis of Project and Terminological Metrics in Project Management 000_11.pdf

This article describes the features of the interaction of participants in the project activity by the example of a large project organization. The model of activities on the basis of metrics version control systems is proposed. The direction of object OWL ontologies application in project activities is also considered. Moreover, an example of the use of ontological structures in solving problems of constructing the unified terminological environment of the project activity in the field of aircraft construction is given. The model of the object ontology of the aircraft flow assembly line (FAL) is proposed by the example of Il-76MD-90A assembly. The experiments of constructing the common terminological basis of the design process by terminology extraction from education materials on corresponding topics in the development of project documentation for the FAL automated management system (FAL AMS) of JSC ‘Aviastar-SP’ are presented.

Project management, version control system, object ontology, terminological environment.

2016_ 4

Sections: Artificial intelligence

Subjects: Artificial intelligence.


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.


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,

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 UlSTU with a specialty of Applied Informatics (in Economics); an author of articles in the field of data mining. [e-mail: timina_i@mail.ru@ulstu.ru]I. Timina

Automated System Model and Control Tools on the Base of Program Code Metrics History 000_10.pdf

The article discusses the issue of project management associated with the development of software products through using automated version control system (VCS) and the analysis of program code metrics. This problem is solved through studying VCS functioning with the further use of the data analysis component of the project management based on the application of the time series (TS) model, the construction of fuzzy TS trends, clustering for dominant fuzzy trends separation, extracting time series predicate, the similarity measure of time series, their correlation, prediction and correction of the forecast. Time series of the number of errors in the total number of changes, the number of improvements in the same number of changes, the number of new functions were used as program code metrics. The hypothesis of the trend permanency was chosen for prediction. The given approach was examined on the examples.

Version control system, time series, fuzzy trend, forecasting, forecast adjustment.

2015_ 3

Sections: Computer-aided engineering

Subjects: Computer-aided engineering, Automated control systems.


Irina Aleksandrovna Timina, Ulyanovsk State Technical University, Post-graduate student at the Department of Information systems at Ulyanovsk State Technical University; graduated from the Faculty of Information Systems and Technology at Ulyanovsk State Technical University with the speciality in Applied Information Science (in Economics); an author of articles and research papers in the field of data mining. [e-mail: timina_i@mail.ru]I. Timina

Fuzzy Dependency As a Problem-solving Method for Time-series Mining 33_6.pdf

The article is concerned with a fuzzy time-series dependency analysis intended for the problem solving of modelling and forecasting of the economic-units behaviour. The problem solving is based on the application of a linear regression model, on the degree of similarity between the time series and their correlation. In order to forecast the value of Fuzzy Time Series, a method of fuzzy elementary tendencies is used. The proposed approach has been examined experimentally.

Fuzzy time series, forecasting, fuzzy tendency.

2013_ 3

Sections: Mathematical modeling, calculi of approximations and software systems

Subjects: Artificial intelligence, Operational research.


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