ISSN 1991-2927
 

ACP № 1 (55) 2019

Keyword: "knowledge base"

Aleksei Sergeevich Katasev, Kazan National Research Technical University named after A.N. Tupolev-KAI, Candidate of Science in Engineering; graduated from the Faculty of Physics and Mathematics of the Elabuga State Pedagogical Institute; Associate Professor of the Information Security Systems Department of the Kazan National Research Technical University named after A.N. Tupolev-KAI; an author of scientific works in the field of mathematical modeling, data analysis and development of intelligent decision support systems. [e-mail: Kat_726@mail.ru]A. Katasev

Neuro-fuzzy Model and Software Complex for Automation of Forming Fuzzy Rules for Objects State Assessing 55_3.pdf

This article deals with the task of objects state assessing in uncertainty. To solve it, the need to use of fuzzy knowledge bases and fuzzy inference algorithms as part of fuzzy expert systems is being actualized. As a tool for a knowledge base formation, a neuro-fuzzy model is proposed. The proposed type of fuzzy rules and the logical inference algorithm on the rules for object state assessing are described. A structure of a fuzzy neural network consisting of six layers is proposed, each of which implements a corresponding stage of the logical inference algorithm. As a result of learning a fuzzy neural network, a system of fuzzy rules is formed, which make up the knowledge base for object state assessing. On the basis of the proposed neuro-fuzzy model, a software complex was implemented for automating the processes of forming fuzzy rules. The main components of the software complex are the knowledge base generation module and the fuzzy inference module. As an approbation of the neuro-fuzzy model, the formation of fuzzy rules for water lines state assessing at the pumping stations in reservoir pressure maintenance systems has been carried out. The results of the testing confirmed the high efficiency of the neuro-fuzzy model and the possibility of its practical use for the formation of fuzzy rules in various subject areas.

Neuro-fuzzy model, fuzzy neural network, fuzzy rules formation, knowledge base, object state assessment, decision-making support.

2019_ 1

Sections: Information systems

Subjects: Information systems.



Aleksei Aleksandrovich Filippov, 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 intelligent systems for data storage and processing. [e-mail: al.filippov@ulstu.ru]A. Filippov,

Anastasiia Vladimirovna Vodovozova, Ulyanovsk State Technical University, Candidate for the Master’s Degree 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 intelligent systems for data storage and processing. [e-mail: nastyavodovozova@mail.ru]A. Vodovozova,

Svetlana Aleksandrovna Makarova, Ulyanovsk State Technical University, Candidate for the Master’s Degree 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 intelligent systems for data storage and processing. [e-mail: makarovasvetlana2025@gmail.com]S. Makarova,

Denis Olegovich Shalaev, Ulyanovsk State Technical University, Candidate for the Master’s Degree 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 intelligent systems for data storage and processing. [e-mail: melges@post.ru]D. Shalaev

Constructing the Fuzzy Domain-specific Knowledge Base on the Basis of Context Analysis 000_12.pdf

The paper discovers the ontology model of the fuzzy domain-specific knowledge base (KB) that allows describing the domain-specific ontology (DSO) according to variety of the DSO contexts. The DSO context is a state of the KB content, which can be selected from a variety of the ontology states. This state is obtained by versioning or organization of the KB content from different points of views. The using of the ontological approach for integration with heterogeneous corporate information resources is also described in the paper. The huge corpora of specialized texts that are connected with the DSO, different types of corporate KB, and wiki-resources are considered as corporate information resources.

Knowledge base, corporate information resources, ontology, context, problem area.

2016_ 4

Sections: Artificial intelligence

Subjects: Artificial intelligence.


Aleksandr Kupriianovich Ivanov, Federal Research-and-Production Center Joint Stock Company ‘Research-and-Production Association ‘Mars’, Doctor of Engineering, Honoured Worker of Science and Engineering of the Ulyanovsk Region; graduated from the Faculty of Physics of Irkutsk State University; finished his postgraduate studies at Bauman Moscow Higher Technical School and his doctoral studies at Ulyanovsk State Technical University; Chief Staff Scientist at Federal Research-and-Production Center Joint Stock Company ‘Research-and-Production Association ‘Mars’; an author of monographs, articles, and the manual in the field of mathematical modeling of hierarchical real-time computer-aided control systems. [e-mail: mars@mv.ru]A. Ivanov

Dynamic Models of Information Processes in Hierarchical Control Systems 000_1.pdf

The dynamic model of situation coverage and control planning processes was constructed on the basis of unified numeration of the hierarchical control system objects. The differential equation system describing information processes was generated for each object of the system. Analytical solutions were obtained for three lower levels of a hierarchy while situation covering and for three upper levels while control planning. Analytical solutions represent dependencies of information resources volumes on time, information processing speed, and initial data volume. The model constructing is based on the condition of information resources volume conservation in case of any transformations. The real ability of the analytical solution of differential equations for objects of all levels is shown. The results of the information processes calculations in two-level systems are considered. The constructed models allow to hold investigations of certain properties of a system promptly and without significant costs in different situations. For examples, such models allow to estimate the control cycle time while changing speed of information processing on objects. On the stages of design, the use of models gives an opportunity to formalize and automate the search of optimal project solutions and provides improvement in quality and losses in cost.

Hierarchical control systems, information processes, differential models.

2016_ 3

Sections: Automated control systems

Subjects: Automated control systems, Mathematical modeling, Information systems.


Aleksandr Kupriianovich Ivanov, Federal Research-and-Production Center Joint Stock Company ‘Research and Production Association ‘Mars’, Doctor of Engineering, Honoured Worker of Science and Engineering of the Ulyanovsk Region; graduated from the Faculty of Physics at Irkutsk State University; finished his post-graduate studies at Bauman Moscow Higher Technical School and his doctoral studies at Ulyanovsk State Technical University; Chief Staff Scientist at Federal Research-and-Production Center Joint Stock Company ‘Research and Production Association ‘Mars’; an author of monographs, articles, and a manual in the field of mathematical modeling of hierarchical real-time computer-aided control systems. [e-mail: mars@mv.ru]A. Ivanov

Automated System of Terror Threats Assessment 000_1.pdf

The author considers the ability to use expert systems in the automated system of terror threats assessment to analyze signs of preparation to commission of terrorist acts and to evaluate threating level. The list of signs of terrorist acts preparation is submitted. These signs include information about facts of terrorist acts preparation, terrorists’ targets and the time of the attacks. The models of developing the expert system knowledge base are offered. The models include random generation of signs and threat assessments corresponding to them. The threat assessments were determined by experienced experts beforehand. Threat assessment automation under actual conditions is implemented through comparison of current characteristics values and characteristics values in the knowledge base and showing the most appropriate variants to the user. The author shows the algorithm of using the expert work in operational activities to assess the real threats in the current conditions and to expand the experience base and training exercises.

Automated system, expert systems, knowledge base, operative research activities, terror threats.

2015_ 2

Sections: Automated control systems

Subjects: Automated control systems, Artificial intelligence.


Sergei Aleksandrovich Ageev, OJSC ‘Research Institute ‘Neptun’, Candidate of Engineering, Associate Professor; graduated from the Faculty of Radio-engineering at Ulyanovsk Polytechnic Institute; Head of the Scientific and Technical Centre OJSC ‘Research Institute ‘Neptun’, St. Petersburg; specializes in the field of telecommunications system design; an author of articles and patents in the field of data-transfer system. [e-mail: serg123_61@mail.ru]S. Ageev

Data Mining Methods for Information Security Risks Management of the Special Purpose Protected Multiservice Networks 000_4.pdf

The data mining methods using for information threat risks management of the special-purpose protected multiservice networks (SPMN) elements are proposed. The fact that the process speed in SPMN, its variety, inaccuracy, and imperfection as well as a high aprior network element data dimension necessitates the application of intelligent techniques for data processing and management is explained. The factors effected on the SPMN information security management cycle time are analyzed, a unified metric for the threat assessment of SPMN elements information security is proposed. A unified mathematical model for the procedure of information security threat clustering, ranking, and classification is developed, its performance criteria are evaluated. The research results of this mathematical model are presented. Threat estimation rules for the special-purpose protected multiservice networks are formulated. The achieved results of mathematical modeling are analyzed, the recommendations of practical application are provided. The similar methods and algorithms application in combination with intelligent agent technology allow to increase the efficiency of SPMN information security management. Directions for future research in this subject domain are defined.

Protected multiservice network, efficiency of the management, tmn-model, mathematical model, intelligent control, fuzzy inference, knowledge base, membership function, fuzzy data, linguistic variable.

2015_ 2

Sections: Information systems

Subjects: Information systems, Mathematical modeling, Artificial intelligence.


Sergey Aleksandrovich Ageev, Military Academy of Communications, Candidate of Engineering, Associate Professor, Advanced Doctoral Student at the Military Academy of Communications (St. Petersburg); graduated from the Faculty of Radio-Engineering of Ulyanovsk Polytechnic Institute; specializes in the field of telecommunications system design; an author of articles and patents in the field of data-transfer system [e-mail: serg123_61@mail.r]S. Ageev,

Igor Borisovich Saenko, St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, Doctor of Engineering, Professor; graduated from the Military Academy of Communications (St. Petersburg); completed his post-graduate and advanced doctoral programs at the same Academy; Professor at the St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences; specializes in the field of creation and development of information-management systems; an author of monographs, articles, and patents in the same field. [e-mail: ibsaen@mail.ru]I. Saenko,

Yuriy Petrovich Egorov, Federal Research-and-Production Center Open Joint Stock Company ‘Research-and-Production Association ‘Mars’, Doctor of Engineering, Professor; graduated from the Faculty of Radio-Engineering of the Admiral Makarov Leningrad Higher Marine School of Engineering; Chief Staff Scientist at Federal Research-and-Production Center Open Joint Stock Company ‘Research-and-Production Association ‘Mars’, Ulyanovsk; specializes in the field of macro-design of large-scale information-management systems; an author of monographs, articles, and patents in the field of computer-aided troop C2 systems design. [e-mail: yupe@mail.ru]Y. Egorov,

Anatoliy Afanasevich Gladkikh, Ulyanovsk State Technical University, Candidate of Engineering; Professor at the Department of Telecommunications of Ulyanovsk State Technical University; graduated from the Marshal Budenny Military Academy of Communications; completed his post-graduate studies at the same Academy; specializes in the field of signal-code sequence synthesis and antinoise coding in telecommunication systems; an author of articles and patents in this subject area [e-mail: a_gladkikh@mail.ru]A. Gladkikh,

Aleksandr Valentinovich Bogdanov, Research-and-Development Center at the Marshal Budenny Military Academy of Communications, Candidate of Military Sciences, Associate Professor, Deputy Head of the Research-and-Development Center at the Marshal Budenny Military Academy of Communications; graduated from Military Academy of Communications; completed his post-graduate studies at the same Academy; specializes in the field of creation and development of information-management systems for communications control. [e-mail: bog-saha@yandex.ru]A. Bogdanov

Intelligent Hierarchical Information Security Risk Management in Protected Special-purpose Multiservice Networks 37_10.pdf

The main approaches to the elaboration of intellectual methods and algorithms synthesized on their base for the assessment and risks management of the information security for protected multi-service networks are considered. The priority for improving such network structures is the efficiency enhancement of the management cycle, the management reliability and the expediency of the responses to the external destructive impact on the network. It is shown that the diversity, the heterogeneity, the incompleteness, the high dimensionality and the inaccuracy of the input data used in the network security management tasks predetermine the necessity of the use of means and methods of the artificial intelligence, in particular, the construction of the prediction analysis generated by the expert, which are formalized as fuzzy sets. Within the framework of this model the hierarchical interaction management tasks are developed and proved. The conceptual provisions of intellectual information security risk management network are provided; the intellectual multi-agent framework for the risk assessment of the network threats as well as the algorithms of their functioning are developed. The study results of the numerical mathematical modeling of the functioning of the intellectual multi agent relating the assessment of the threats to the information network security network are presented.

Telematic network services, tmn model, intelligent management, fuzzy inference, knowledge base, linguistic variable.

2014_ 3

Sections: Artificial intelligence

Subjects: Artificial intelligence, Automated control systems, Architecture of ship's system.


Anatoly Alexanderovich Kupriyanov, FRPC OJSC RPA Mars, Candidate of Engineering, Associate Professor, graduated from the Faculty of Radio-Engineering at Ulyanovsk Polytechnic Institute; leading staff scientist at FRPC OJSC RPA Mars; interested in the field of methodology of creation and building of distributed computer systems; author of papers and articles in design and development of local and corporate networks, computer-aided packages, and special- and general-purpose computer-aided control systems. [e-mail: aakupr1828@rambler.ru.]A. Kupriyanov,

Anatoly Stepanovich Melnichenko, Ulyanovsk State University, Graduated from the Faculty of Automated Mechanisms and Computers at Moscow Rail-Transport Engineer College; senior lecturer at the Chair Telecommunications Technologies and Networks of Ulyanovsk State University; specializes in the field of modeling of technological-preparation processes of development of software and expert systems; author of papers and articles in the field of software engineering. [e-mail: masulgu@yandex.ru]A. Melnichenko

Approaches to Intellectualization of System-engineering Processes of Computer-aided Systems 24_8.pdf

The article deals with theoretical, practical and organizational aspects of intellectualization of system-engineering processes in life cycle of computer-aided systems. It also presents models of quality assessment for design decisions and technological maturity of design and development processes of computer-aided systems.

Computer-aided system, knowledge base, intellectualization, meta-process, multivariate model, design decision (artifact), system engineering, template repository.

2011_ 2

Sections: Integrated command and control systems. ships complexes and systems

Subjects: Computer-aided engineering, Automated control systems.


Anatoly Alexanderovich Kupriyanov, [e-mail: mars@mv.ru ]A. Kupriyanov,

Anatoly Stepanovich Melnichenko[e-mail: mars@mv.ru ] A. Melnichenko

Intellectual Object-oriented Analysis, Design and Development of Computer-aided Systems 21_6.pdf

The article is devoted to issues of mining and representation of knowledge in processes of object-oriented analysis, design and development of computer-aided systems. The subject of investigation is knowledge base of knowledge domain in objectoriented form. The article deals with features of knowledge-base use during decision-making by concerned persons during the design of a computer-aided system. It also stresses issue of the use of ontology of knowledge domain, defines an approach to the creation of computer-aided system of knowledge domain taking into account state-of-the-art trends in information science and technologies.

Knowledge, knowledge control, knowledge representation, knowledge base, virtual enterprise, object-oriented analysis, ontology, knowledge domain, service-oriented technologies, multiagent systems, ontological engineering.

2010_ 3

Sections: System analysis, data management and processing

Subjects: Automated control systems, Architecture of ship's system.


Aleksei Arkadevich Smagin, [e-mail: mars@mv.ru] A. Smagin,

Svetlana Valerevna Lipatova, [e-mail: mars@mv.ru] S. Lipatova,

Evgenii Serafimovich Kukin, [e-mail: mars@mv.ru] E. Kukin

Development of Knowledge Base for Sea Monitoring Expert System 18_5.pdf

The article suggests a heterogeneous graph with four node types which are organized by layers, to be used as a design method of production knowledge base of expert sys-tem. It also deals with an algorithm of production graph creation and formalization of typical situations.

Expert systems, knowledge bases, sea monitoring.

2009_ 4

Sections: Issues of interaction and decision-making support in integrated command and control systems

Subjects: Artificial intelligence, Automated control systems, Architecture of ship's system.


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