ISSN 1991-2927
 

ACP № 3 (61) 2020

Author: "Nadezhda Glebovna Yarushkina"

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Nadezhda Glebovna Yarushkina, Doctor of Sciences in Engineering, Professor; graduated from Ulyanovsk Polytechnic Institute with the specialty in Electronic Computing Machines; Head of the Department of Information Systems at Ulyanovsk State Technical University; an author of more than 400 papers in the field of soft computing, fuzzy logic, and hybrid systems. e-mail: jng@ulstu.ruN.G. Yarushkina

Vadim Sergeevich Moshkin, graduated from the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University; Associate Professor of the Department of Information Systems of UlSTU; an author of more than 90 papers in the field of data analyzing intelligent systems. e-mail: v.moshkin@ulstu.ruV.S. Moshkin

Andrei Alekseevich Konstantinov, a student in the master’s degree at the Department of Information Systems of Ulyanovsk State Technical University; an author of articles in the field of text mining; the area of his scientific interests relates to the automation of text analysis using machine learning. e-mail: adwaises@mail.ruA.A. Konstantinov

Word2vec and BERT language models used for a sentiment analysis of text posts in social networks61_7.pdf

The paper proposes an original algorithm for the formation of a training sample for a neural network that provides a sentiment analysis of text posts in social networks. A feature of the algorithm is the use of the extended Russian-language semantic thesaurus WordNetAffect and the expert dictionary of author’s symbols for expressing emotions. In addition, the paper describes the application of a neural network based on the LSTM architecture to determine the emotional coloring of text messages on a social network using two text vectorization algorithms “word2vec” and “BERT”. As a result of the experiments, an indicator of the accuracy of determining the emotional coloring of messages of 87% was achieved using lemmatization as a text preprocessing algorithm and the BERT algorithm when converting it into a vector.

Sentiment analysis, BERT, word2vec, neural network, social network.

2020_ 3

Sections: Artificial intelligence

Subjects: Artificial intelligence.

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Anton Alekseevich Romanov, Candidate of Sciences in Engineering; graduated from the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University (UlSTU); Associate Professor of the Department of Information Systems at UlSTU; an author of articles in the field of intelligent systems for data storage and processing. e-mail: romanov73@gmail.comA. A. Romanov

Aleksei Aleksandrovich Filippov, Candidate of Sciences in Engineering; graduated from the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University; Associate Professor of the Department of Information Systems at UlSTU; an author of articles in the field of ontological modeling, intelligent systems for data storage and processing. e-mail: al.filippov@ulstu.ruA. A. Filippov

Nadezhda Glebovna Yarushkina, Doctor of Sciences in Engineering, Professor; graduated from Ulyanovsk Polytechnic Institute; Interim Rector of Ulyanovsk State Technical University, Head of the Department of Information Systems at UlSTU; an author of more than 300 scientific papers in the field of soft computing, fuzzy logic, and hybrid systems. e-mail: jng@ulstu.ruN. G. Yarushkina

Vladimir Anatolyevich Maklaev, Candidate of Sciences in Engineering; graduated from Radioengineering Faculty of Ulyanovsk Polytechnic Institute; Director General of Federal Research-and-Production Center Joint-Stock Company ‘Research-and-Production Association ‘Mars’. The area of scientific interests relates to the computer- aided design systems. e-mail: mars@mv.ruV. A. Maklaev

The decision support module of information environment for technological support of production60_7.pdf

Making management decisions requires a specialist to have extensive knowledge of the problem area and the current state of the organization. There is a need for timely and urgent management decision support in the activity of any large organization. The decision support module (DSM) was created to solve that kind of problem in the task of balancing production capacities. The main task of the DSM is a linguistic summarization of the state of the main production indicators and the formation of recommendations that allow the decision-maker to develop a specific strategy for balancing production capacities. The DSM functionality is based on the knowledge base in the form of ontology with the set of expert SWRL-rules. This article describes methods for modeling and forecasting the dynamics of the main production indicators based on type- 2 fuzzy sets, and the approach to summarizing the time series of production indicators and forming recommendations for optimizing production based on knowledge engineering methods.

Data-driven decision making, type-2 fuzzy sets, time series forecasting, ontology, inference.

2020_ 2

Sections: Artificial intelligence

Subjects: Artificial intelligence.

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Nadezhda Glebovna Yarushkina, Doctor of Sciences in Engineering, Professor; graduated from Ulyanovsk Polytechnic Institute; Interim Rector of Ulyanovsk State Technical University, Head of the Department of Information Systems at UlSTU; an author of more than 300 scientific papers in the field of soft computing, fuzzy logic, and hybrid systems. e-mail: jng@ulstu.ruN.G. Yarushkina

Aleksei Sergeevich Zhelepov, Postgraduate Student at the Department of Information Systems of UlSTU; graduated from the Faculty of Information Systems and Technologies of UlSTU; a winner of the iVolga-2014 Youth Forum, a coordinator of the “Stachka” IT-Conference, an author of articles in the field of data mining. e-mail: a.zhelepov@gmail.comA.S. Zhelepov

A prototype of a system for searchning and selecting the ‘staffed’ teams of it-professionals based on data from project repositories59_11.pdf

The growth of information technology sphere leads to a serious shortage of qualified personnel. Thus, many companies are changing well-established workflow models, e.g. giving employees the ability to work remotely. That happens due to the opportunity of hiring globally. For companies focused on the development of product solutions, there is a trend of searching for “played” project teams, specialists who have successfully worked together for a long time. However, the search for such teams leaves a definite imprint on the activities of the HR department of the company: it becomes necessary to analyze the activities and technical developments of not individual employees, but of the potential team as a whole. The article describes a prototype of an automated system which main task is to search and select teams of specialists based on data from open source code repositories and related artifacts. The article details: the composition of the system architecture, the selection algorithm for the main project team, identified during the study of the group activity metrics, formulas for calculating the values of the metrics, as well as their application in solving the problem of analyzing the project repository.

Repository, remote development team, teamwork metrics, search, filtering.

2020_ 1

Sections: Computer-aided engineering

Subjects: Computer-aided engineering.

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Vladislav Valerevich Moiseev, Postgraduate Student at the Department of Information Systems of Ulyanovsk State Technical University; graduated from the Faculty of Information Systems and Technologies of UlSTU; a lecturer at the College of Economics and Informatics of UlSTU; an author of articles in the field of data integration. e-mail: v.v.moiseev@ulstu.ruV.V. Moiseev,

Nadezhda Glebovna Yarushkina, Doctor of Sciences in Engineering, Professor; graduated from Ulyanovsk Polytechnic Institute; Acting Rector of UlSTU, Head of the Department of Information Systems at UlSTU; an author of more than 300 publications in the field of soft computing, fuzzy logic, and hybrid systems. e-mail: jng@ulstu.ruN.G. Yarushkina

Initial domain data model based on relational database58_5.pdf

This article describes the data model for obtaining information about the structure of a relational database. This model is useful for the task of reducing labor costs when designing and redesigning the existing software products. Currently, these processes are often accompanied by analysis of excessively large relational schemes, which ultimately increases development time. The model presented in the paper allows one to obtain data from a relational scheme that can subsequently be used to compile other more flexible formalizations. In addition, the model is expandable with extra parameters that cannot be obtained from the relational scheme, but which will be useful for the design task. The paper presents queries in SQL language for obtaining data on the structure of a relational database using the example of the SQL Server database management system and provides a comparative analysis of the proposed scheme in terms of volume and speed of formation with popular formats: DBML and EDMX.

Relational data schema, data model, SQL Server, EDM, DBML.

2019_ 4

Sections: Information systems

Subjects: Information systems.

Eduard Dmitrievich Pavlygin, Federal Research-and-Production Center Joint Stock Company ‘Research-and-Production Association ‘Mars’, Candidate of Science in Engineering; graduated from the Radioengineering Faculty of Ulyanovsk Polytechnic Institute; First Deputy of Director General in Scientific Affairs and Innovations of Federal Research-and-Production Center Joint Stock Company ‘Research-and-Production Association ‘Mars’; an author of articles in the field of statistical methods of signal processing. [e-mail: mars@mv.ru]E. Pavlygin,

Anatolii Gennadievich Podloboshnikov, Federal Research-and-Production Center Joint Stock Company ‘Research-and-Production Association ‘Mars’, graduated from the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University; Head of the Research Laboratory and Chief Designer at FRPC JSC ‘RPA ‘Mars’; research interests are in the field of special-purpose information system. e-mail: mars@mv.ruA. Podloboshnikov,

Ruslan Anatolevich Savinov, Federal Research-and-Production Center Joint Stock Company ‘Research-and-Production Association ‘Mars’, graduated from the Machine-building Faculty of UlSTU; Software Engineer at FRPC JSC ‘RPA ‘Mars’. research interests are in the field of special-purpose information system. [e-mail: mars@mv.ru]R. Savinov,

Nadezhda Glebovna Yarushkina, Ulyanovsk State Technical University, Doctor of Science in Engineering, Professor; graduated from Ulyanovsk Polytechnic Institute; First Vice-Rector, Vice-Rector in Scientific Affairs in UlSTU, Head of the Department of Information Systems at UlSTU; an author of more than 300 publications in the field of soft computing, fuzzy logic, and hybrid systems. [e-mail: jng@ulstu.ru]N. Yarushkina,

Aleksei Mikhailovich Namestnikov, Ulyanovsk State Technical University, Doctor of Science in Engineering, Associate Professor; graduated from the Radioengineering Faculty of UlSTU; an author of more than 80 publications in the field of computer-aided design and intelligent systems.[e-mail: nam@ulstu.ru]A. Namestnikov,

Aleksei Aleksandrovich Filippov, Ulyanovsk State Technical University, Candidate in Science in Engineering; graduated from the Faculty of Information Systems and Technologies of UlSTU; Associate Professor at the Department of Information Systems of UlSTU; an author of articles in the field of ontological modelling and building of computer-aided systems for knowledge processing. [e-mail: al.filippov@ulstu.ru]A. Filippov,

Anton Alekseevich Romanov, Ulyanovsk State Technical University, Candidate of Science in Engineering; graduated from the Faculty of Information Systems and Technologies of UlSTU; Associate Professor at the Department of Information Systems of UlSTU;an author of articles in the field of systems for data storage and processing, and time series mining. [e-mail:romanov73@gmail.com]A. Romanov,

Vadim Sergeevich Moshkin, Ulyanovsk State Technical University, Candidate of Science in Engineering; graduated from the Faculty of information systems and Technologies at UlSTU; Associate Professor of Information Systems at UlSTU; an author of more than 70 articles in the field of data mining systems. [e-mail: postforvadim@ya.ru]V. Moshkin,

Gleb Iurevich Guskov, Ulyanovsk State Technical University, graduated from the Faculty of information Systems and Technologies of UlSTU; Senior Lecturer at the Department of Information Systems of UlSTU; an author of publications in the field of ontological engineering and data mining systems. [e-mail: g.guskov@ulstu.ru]G. Guskov,

Maria Sergeevna Grigoricheva, Ulyanovsk State Technical University, Postgraduate Student at the Department of Information Systems of UlSTU; graduated from the Faculty of Information Systems and Technologies of UlSTU; Assistant Lecturer at the Department of Information Systems of UlSTU; an author of publications in the field of data mining. [e-mail:gms4295@mail.ru]M. Grigoricheva

Development of a Software Package for Data Mining of Social Media56_3.pdf

The article presents the results of work on a software package for data mining of social media. The architecture of the software package is described. Listed the main subsystems of the software package and third-party software systems used in the development of a software package. The organization of the data storage subsystem of the software package is considered, the data model of this subsystem is described. The approach to organizing the ontology repository of a software package based on a graph database is described, and the ontology translation method in the OWL / XML format into a graph database fragment is presented. The organization of the data search subsystem is considered, the method of extending the search query using ontology for accounting for the features of the subject area in the search process is described. Also presented is a method of formatting a search query to highlight the important elements of the query to improve the quality of the search. The organization of the social portrait building subsystem of the user of the social network VKontakte is described, the method of determining the categories of interests of the user is considered.

Social media, ontological analysis, natural language processing, data mining, software package.

2019_ 2

Sections: Information systems

Subjects: Information systems, Artificial intelligence.



Pavel Vladimirovich Dudarin, Ulyanovsk State Technical University, Postgraduate Student at the Department of Information Systems of Ulyanovsk State Technical University (UlSTU); graduated from the Ulyanovsk State Technical University; an author of papers in the field of text clustering. [e-mail: PDudarin@ibs.ru]P. Dudarin,

Aleksandr Petrovich Pinkov, Ulyanovsk State Technical University, Candidate of Economics, graduated from Ulyanovsk branch of Kuibyshev Planning Institute; Acting Rector of Ulyanovsk State Technical University, an author of more than 50 papers, a monograph, and articles in the field of economics, planning, marketing, production engineering, higher education organization, and corporate training. [e-mail: rector@ulstu.ru]A. Pinkov,

Nadezhda Glebovna Yarushkina, Ulyanovsk State Technical University, Doctor of Engineering, Professor; First Vice-Rector - Vice-Rector for Scientific Affairs of Ulyanovsk State Technical University; Head of the Department of Information Systems of UlSTU; graduated from Ulyanovsk Polytechnic Institute; an author of more than 300 papers in the field of soft computing, fuzzy logic, and hybrid systems. [e-mail: jng@ulstu.ru]N. Yarushkina

Methodology and the Algorithm for Clustering Economic Analytics Object 000_12.pdf

The purpose of the study, the results of which are described in the article, consist in developing new and modified methods and algorithms for solving the problem of clustering objects of economic analytics. The use of known algorithms for clustering formulations of economic indicators in order to determine the similarity of objects is complicated by the fact that the formulation of indicators are very short and the traditional indicators of terms occurrence (frequency) are inadequate. In addition, widespread occurrence of interviews and various forms of questionnaires in economic analysis implies the use of linguistic estimates. For example, "customer satisfaction level" indicator is difficult to quantify, so, instead of conventional points, fuzzy values such as “high”, “medium”, “low” are often used. As a result, it becomes feasible to use a fuzzy variant of the k-means method - the method of fuzzy k-means. Typically, the number of indicators in economic analysis is quite big, which makes it advisable to modify the algorithm on the basis of parallel execution. The study addresses the following issues: the k-means method is modified, it is adapted to the characteristics of the economic analytics objects; the methodology of data preprocessing for clustering is developed; new versions of clustering objects of economic analytics are developed, and experimental research of the effectiveness of the developed methods for large volumes of data is carried out.

Fcm-алгоритм, clustering, method of k-means, economic analysis, big data, fcm-algorithm, parallelization.

2017_ 1

Sections: Artificial intelligence

Subjects: Artificial intelligence.


Elena Iurevna Barabanova, Federal Research-and-Production Center Joint Stock Company ‘Research-and-Production Association ‘Mars’, Postgraduate Student at the Department of Information Systems of Ulyanovsk State Technical University; Industrial Engineer at the Department of Chief Industrial Engineer of Federal Research-and-Production Center Joint Stock Company ‘Research-and-Production Association ‘Mars’; an author of articles in the field of automation of control processes of operations planning. [e-mail: mars@mv.ru]E. Barabanova,

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

Estimation of Cam-education Effectiveness With the Use of the Modified Moving Approximation Transform 000_8.pdf

This article offers the new measured estimation of CAM-processing teaching on the basis of the proposed efficiency coefficient. The authors describe the existing approaches to estimation of education effectiveness in general case. The necessity of designing the approach to efficiency estimation of CAM-education with the use of methods for time series data mining is proven. The features of creation of the special education course for CAM-specialists with its estimation are investigated. The CAM-processing metric applied either in education course development or the subsequent estimation of its effectiveness is defined. The proposed hypotheses were checked with the use of real data in the practical experiment on the developed model approbation. Moreover, the features of developing the efficient educational program for teaching mechanical engineering students were considered. The model of CAM-education effectiveness estimation with the use of the modified Moving Approximation Transform was proposed.

Effectiveness, cam-education, process model, control program.

2016_ 4

Sections: Computer-aided engineering

Subjects: Computer-aided engineering.


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; 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,

Evgenii Nilolaevich Egov, Ulyanovsk State Technical University, Postgraduate Student and Assistant 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: e.egov@ulstu.ru]E. Egov

The Algorithm for Identifying New Anomalies in Technical Time Series Diagnosis 000_4.pdf

The article discusses the ways to diagnose the time series in order to detect anomalies in them. The authors propose to determine the number of each point of the values of the two parameters. Also a set of situations related to changes in the values of these parameters between the points should be prepared. While analyzing series, the frequency of each situation occurrence should be determined. If the probability of situations occurrence is less than 0.01, then such situations may be attributed to an abnormal ones. On the basis of the previous situation choice, a template that allows identifying these anomalies in the future is created. As one of the pairs for situations identification, the entropy measures values obtained from fuzzy time series are proposed to use. The first measure of entropy is calculated by the value of the membership function point compared to the fuzzy label. The second measure of entropy is calculated on the basis of the deviation of the actual value trends from the forecasting one. Series analysis is performed on the basis of the second pair. This pair represent “fuzzy label - fuzzy trend” one. This pair was introduced to identify long-term stay in the areas of certain states, which can be attributed to the abnormal ones. It also describes the algorithm to identify previously unknown anomalies and search of anomalies patterns. The experiment was carried out in order to check the efficiency of the algorithm. Time series of physical quantities characterizing work of important units of helicopter engines in which it was necessary to reveal the presence of defects were investigated. The main interest of this paper is the anomaly detection algorithm based on the measure of the uncertainty of the time series. The article is intended for professionals diagnosing technical systems.

Entropy measure, diagnosis, time series, anomalies.

2016_ 2

Sections: Information systems

Subjects: Information 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.


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.


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, 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,

Tatiana Vasilevna Afanaseva, Ulyanovsk State Technical University, Doctor of Engineering; Associate Professor, Deputy Head of Information Systems Department at Ulyanovsk State Technical University; graduated from the Faculty of Radioengineering at Ulyanovsk State Technical University; an author of articles and monographs in the field of time series data mining. [e-mail: tv.afanasjeva@gmail.com]T. Afanaseva,

Aleksei Mikhailovich Namestnikov, Ulyanovsk State Technical University, Candidate of Engineering, Associate Professor, Associate Professor at the Department of Information Systems at Ulyanovsk State Technical University; graduated from the Faculty of Radioengineering of Ulyanovsk State Technical University; an author of articles and a monograph in the field of intelligent systems for storage and processing of information. [e-mail: nam@ulstu.ru]A. Namestnikov,

Gleb Iurevich Guskov, Ulyanovsk State Technical University, Post-Graduate Student of the Department of Information Systems at Ulyanovsk State Technical University; graduated from the Faculty of Information Systems and Technologies at Ulyanovsk State Technical University; an author of articles in the field of time series data mining. [e-mail: guskovgleb@gmail.com]G. Guskov

Integration of Fuzzy Granular and Ontological Methods for Time Series Analysis 000_8.pdf

The theoretical and methodological foundations of fuzzy granular modeling were developed to solve the problem of fuzzy trend analysis of time series. Their practical implementation as a program complex allows to get the solution of some applied problems. Fuzzy granular presentation of time series includes five levels: from numeric value granulation to the main trend granulation. The authors propose to use fuzzy ontologies of problem area to interpret the results of time series analysis. he problem area fuzzy ontologies were offered to interpret the results of time series analysis. The ontology basis is based on the RDF model that defines classes, instances, ontological relationships, and contingencies. The logical interference of recommendation is realized on the basis of interaction between fuzzy OWL ontology and rule-oriented SWRL rules system. The article deals with the possibilities of integration of several methods of time series forecasting and corresponding aggregates. The integration of techniques for time series analysis and ontological analysis demonstrates the competitiveness of fuzzy trend models based on the mutual reinforcement of ontological and fuzzy granular methods.

Fuzzy time series, fuzzy tendencies, ontology, fuzzy ontology.

2015_ 2

Sections: Information systems

Subjects: Information systems, Artificial intelligence.


Ilya Alekseevich Andreev, Ulyanovsk State Technical University, a student at the Faculty of Information Systems and Technologies at Ulyanovsk State Technical University; an author of several articles in the field of information extraction from text. [e-mail: ares-ilya@yandex.ru]I. Andreev,

Vitaliy Aleksandrovich Bashaev, Ulyanovsk State University, a post-graduate student; graduated from the Faculty of Linguistics and International Cooperation of Ulyanovsk State University; an author of several articles in the field of information extraction from text. [e-mail: perevod73@yandex.ru]V. Bashaev,

Victor Victorovich Klein, Ulyanovsk State Technical University, a student at the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University; an author of several articles in the field of information extraction from text. [e-mail: vikklein93@gmail.com]V. Klein,

Vadim Sergeevich Moshkin, Ulyanovsk State Technical University, a post-graduate student at the Department of Information Systems of Ulyanovsk State Technical University; graduated from the Faculty of Information Systems and Technologies at Ulyanovsk State Technical University; an author of articles in the field of data analysis intelligence systems. [e-mail: postforvadim@yandex.ru]V. Moshkin,

Nadezhda Glebovna Yarushkina, Ulyanovsk State Technical University, Doctor of Engineering, Professor, Head of the Department of Information Systems at 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

A Semantic Metric of the Termhood Based on the Subject Area Ontology 38_10.pdf

The article describes a semantic metric for a retrieval of a list of terms from the texts of a specific knowledge domain, based on the analysis of its ontology. A formal model of the used OWL-ontology, as well as models and algorithms for the degree evaluation of a word termhood or word combinations of text arrays are presented. In addition, the evaluation metrics of the presented semantic algorithms performance are given. The implementation of the formal models of a domain knowledge representation in an ontological form and the algorithms developed in the software system for the terminology extraction from the text is considered. In conclusion, the results of the computational experiments performed for the extraction of terms based on the ontology of the NC turning-milling machine operation from the texts of an appropriate knowledge domain are provided. A conducted research is summarized. The most efficient algorithms for the degree evaluation of a word termhood or word combinations are revealed, and a perspective for further scientific research in this area is examined.

Term extraction, semantic metric, ontology.

2014_ 4

Sections: Artificial intelligence

Subjects: Artificial intelligence.


Vadim Sergeevich Moshkin, 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 of Ulyanovsk State Technical University; an author of articles in the field of intelligent systems. [e-mail: postforvadim@yandex.ru]V. Moshkin,

Nadezhda Glebovna Yarushkina, Ulyanovsk State Technical University, Doctor of Engineering, Professor, Head of the Department of Information Systems at 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

Ontological Time-series Analysis System 36_12.pdf

This article describes a semantic approach to analyzing the time series as an example of local area network (LAN) status parameters using the ontology of problem area. We represent a formal model of the OWL-ontology for the considered subject domain, an ontological view model for a set of production rules. An inference algorithm for LAN architecture modification during its status estimation while artificially increasing traffic is proposed.We solved the aggregation problem of the different approaches to expert knowledge representation through the product knowledge integration into the ontological model using SWRL- rules. In addition, the implementation of this algorithm in the time-series analysis software TSAnalyzer is considered.The results of computational experiments on LAN-status simulation while artificially increasing traffic as an example of the LAN of the Center for Development of Electronic Media Technologies at Ulyanovsk State Technical University are represented. We summarized the research results conducted and evaluated further research findings expectation in this domain.

Ontology, time series, data mining, semantics.

2014_ 2

Sections: Artificial intelligence

Subjects: Artificial intelligence, Automated control systems.


Ilia Alekseevich Andreev, Ulyanovsk State Technical University, a student of the Faculty of Information Systems and Technologies at Ulyanovsk State Technical University; an author of several articles in the field of information extraction from a text. [e-mail: ares-ilya@yandex.ru]I. Andreev,

Vitalii Aleksandrovich Bashaev, Ulyanovsk State Technical University, a post-graduate student, graduated from the Faculty of Linguistics and International Cooperation at Ulyanovsk State University; an author of articles in the field of information extraction from a text. [e-mail: perevod73@yandex.ru]V. Bashaev,

Victor Victorovich Klein, Ulyanovsk State Technical University, a student of the Faculty of Information Systems and Technologies at Ulyanovsk State Technical University; an author of several articles in the field of information extraction from a text. [e-mail: vikklein93@gmail.com]V. Klein,

Nadezhda Glebovna Iarushkina, Ulyanovsk State Technical University, Doctor of Engineering, Professor, Head of the Department of Information Systems at Ulyanovsk State Technical University; an author of more than 250 papers in the field of soft computation, fuzzy logic, and hybrid systems. [e-mail: jng@ulstu.ru]N. Iarushkina

Combining Statistic and Linguistic Methods to Exstract Two-word Terms From a Text 34_11.pdf

This article contains the experiment results on the combination of linguistic and statistical methods for extraction of two-word terms from a text on "CnC Machines" discipline. Along with the experiment and the results, a special attention is paid to the description of the developed software architecture.

Term extraction, linguistic method, statistic method, bigrams frequency.

2013_ 4

Sections: Artificial intelligence system

Subjects: Artificial intelligence, Information systems.


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, a text-book in the field of intellectual analysis of time series. [e-mail: tv.afanaseva@mail.ru]T. Afanasyeva,

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

Efficiency Analysis of Fuzzy Trend Model for Forecasting of Time Series 26_7.pdf

The article describes a new model for the analysis of time series for the forecast of small time series. The base of the new model is formalization and identification of a new object of time series - a fuzzy trend. The suggested model does not have assumptions used in stochastic simulation, and is easy for the implementation and developed for linguistic interpretation of results. The experiment studies of the accuracy figures of the suggested model reveal its adequacy for forecasting of small time series and competitiveness in comparison with its analogues.

Forecasting, time series, fuzzy trend, accuracy figures.

2011_ 4

Sections: Artificial-intelligence systems

Subjects: Artificial intelligence, Automated control systems, Mathematical modeling.


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, Ulyanovsk State Technical University, Doctor of Engineering, Professor, graduated from the Faculty of Radio-Engineering at the Ulyanovsk Polytechnic Institute; Pro-Rector for Science; holds the Chair Information Systems at the Ulyanovsk State Technical University; author of articles and monographs in the field of intellectual analysis of data. [e-mail: jng@ulstu.ru]N. Yarushkina

Intellectualization of Cad for Complex Technical Systems Under Uncertain Conditions 23_2.pdf

This article deals with basic steps and development of intellectualization of CAD-systems for complex technical systems though basic paradigms. The specific feature of the article consists in the following: the manifestation of basic paradigms is shown on basis of problem-oriented systems developed by the Ulyanovsk State Technical University in cooperation with FRPC OJSC RPA Mars during the last 25 years. The cooperation, unique from the point of view of its duration, allows seeing how the embedded intelligence of particular developments grew, and is reasonably reflected in the chronological order of the article content.

Intellectual cad-system, knowledge engineering, soft computing, computational intelligence, soft expert-system, fuzzy tendency of time series.

2011_ 1

Sections: Computer-aided design systems

Subjects: Artificial intelligence, Automated control systems, Computer-aided engineering.


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

Aleksandra Valerevna Chekina[e-mail: mars@mv.ru] A. Chekina

Clustering of Information Resources on Basis of Genetic Algorithm 22_12.pdf

The article offers a solution method for the task of clustering of electronic information resources on basis of genetic algorithm. All the documents from project repository are described by frequency distributions of met terms. Input data are presented by genetic-algorithm structures.

Informational resource, clustering, indexing, genetic algorithm, crossover, suitability function.

2010_ 4

Sections: Artificial-intelligence systems

Subjects: Artificial intelligence.


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

Tatiana Vasilievna Afanaseva, [e-mail: mars@mv.ru] T. Afanasyeva,

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

Integral Method of Fuzzy Modeling and Analysis of Fuzzy Tendencies 20_9.pdf

The article deals with a new method of modeling of time series, which integrates intel-lectual methods of task solution concerning knowledge extraction from time series not only in numerical form but also in the form of linguistic description of levels and elementary tendencies.

Fuzzy model, time series, fuzzy tendency, knowledge extraction, forecast.

2010_ 2

Sections: Theoretical issues of automation of command and control processes

Subjects: Artificial intelligence.


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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