ISSN 0236-235X (P)
ISSN 2311-2735 (E)

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Publication date:
16 March 2018
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Journal articles №4 2017

1. Program synthesizing based on a graph-analytic model description [2017-11-28]
Authors: A.G. Zykov (zykov_a_g@mail.ru) - The National Research University of Information Technologies, Mechanics and Optics, Ph.D Ph.D; I.V. Kochetkov (melmacson@gmail.com) - The National Research University of Information Technologies, Mechanics and Optics, ; V.I. Polyakov (v_i_polyakov@mail.ru) - The National Research University of Information Technologies, Mechanics and Optics, Ph.D Ph.D; E.G. Chistikov (frazer@list.ru) - The National Research University of Information Technologies, Mechanics and Optics, Undergraduate Undergraduate;
The quantity and volumes of the developed software grow annually. It stimulates developers to create new tools enabling to reduce time for the next product development. It also includes testing automation equipment. The demand for new instruments of test automation increases due to increasing number of systems using different programming lan-guages. The relevance of the task of searching universal cross-language testing tools remains high. The paper considers verification of computing processes based on a graph-analytic model (GAM). The key idea of this approach is that the developed program is converted into a GAM description and is compared to the reference GAM description according to which it was created. Further, according to the results of comparing, the program either is recognized as correct, or is sent back for revision. A bottle neck of such approach is development of the program based on GAM and a potential iteration nature of the process. The authors suggest a special utility to solve this problem. This utility performs synthesis of programs for reference descriptions. The paper considers an algorithm of conversion of a GAM description object model into text representation of C# operators and expressions. A research objective is automation of program synthesis in C# by a group of GAM descriptions of a computing process. Within the research, we have created a tool enabling to transform GAM descriptions into program source codes. We have checked the developed utility on GAM descriptions of an array processing program (sorting, turn). The synthesized executed module has been successfully tested in Windows 10 operating system environment. In the future we plan to develop the utility along with new versions of a description language to enrich the possibilities of synthesizable programs.
Keywords: verification, testing, automation, program synthesis, generation of programs, roslyn, graph-analytic model
Visitors: 549

2. Interval differential equations in kalman fuzzy filter structure in complex technological object management [2017-11-28]
Authors: A.Yu. Puchkov (putchkov63@mail.ru) - Smolensk Branch of the Moscow Power Engineering Institute, Ph.D Ph.D; Dli M.I. (midli@mail.ru) - (Smolensk Branch of the Moscow Power Engineering Institute, Ph.D Ph.D;
The paper proposes an estimation technique of processes in complex technological objects based on using interval methods in a differential vector-matrix equation that describes Kalman filter. In contrast to methods for solving a differential equation that describes Kalman filter, in real numbers interval notation allows taking into consideration input data uncertainty and inexactness due to different factors. Such factors include measuring equipment errors depending on instrument rating, round-off errors in numerical calculation, time and amplitude sampling errors. Inexactness also depends on mathematical methods, such as using a fuzzy logical approach in forming filter matrix determination when describing processes in complex technological objects. This is due to subjectivity in forming fuzzy model parameters: kinds of membership functions, a number of variable therms, rules of knowledge base filling. The novelty of the proposed approach is in the developed technique of process state interval estimations in conditions of input data inexactness based on interval differential equations methods. The methods allow reducing solving differential equations to more simplified system of solving polynomial equation. The paper reviews the steps of solving the equation that determines Kalman filter. The steps consist of a transition from a differential vector-matrix filter equation to a scalar form, then to an interval differential form and a system of polynomial equations. The solution of this system presents the desired range of process state estimations. The paper shows an exemplification and results of a MATLAB program work based on the proposed technique.
Keywords: fuzzy logic, Kalman filter, interval differential equations, inexact input data
Visitors: 578

3. Modular computer systems simulation software tool for checking feasibility of their configurations [2017-11-28]
Author: A.B. Glonina (alevtina@lvk.cs.msu.su) - Lomonosov Moscow State University ;
The paper presents a software tool for checking feasibility of real-time modular computer systems (RT MCS) configuration. Integrated modular avionics (IMA) systems are considered as an example of RT MCS. An RT MCS configuration is feasible if all works for all computational tasks complete within their deadlines. The author formulates a set of requirements to configurations feasibility checking tool based on analysis of RT MCS design problems. The review of the existing software tools has shown that none of them satisfies all the requirements. Thus, it has become necessary to develop our own tool that would satisfy all the requirements. The proposed software tool allows simulating RT MCS and obtaining timing diagrams of their operation, which are necessary for feasibility checking. The correctness of the developed models was formally proven due to the chosen mathematical formalism (stopwatch time automata networks). As a model for a given configuration can be built and run automatically, our tool can be used together with the optimal configurations search algorithm. The tool was integrated with the scheduling CAD system into the industrial RT MCS and tested on realistic datasets. The experiments showed that the tool is suitable for practical use. Moreover, it is more efficient then a MCS model that is built into a CAD system for the configurations with long scheduling interval. Furthermore, in contrast with the proposed tool, the CAD system model does not satisfy all the requirements.
Keywords: correctness, verification, scheduling, simulation, integrated modular avionics, time automata networks
Visitors: 480

4. Interpretation of the meaning of natural language phrases in problem-oriented systems [2017-11-28]
Authors: Billig V.A. (Vladimir-Billig@yandex.ru) - Tver State University, Ph.D Ph.D; I.S. Smirnov (dru0121@gmail.com) - Tver State Technical University, Undergraduate Undergraduate;
The organization of a natural language dialog with a computer is one of the most important problems in the field of artificial intelligence. The expressive power of a natural language makes it difficult to formalize and eliminate ambi-guities in understanding phrase meanings. This article considers the approach to interpreting natural language phrases based on the “Meaning–Text” theory. The key point is an intentional dialogue context limitation with a specified domain. This allows the system to conduct a more meaningful dialogue and to solve specific problems of the given domain. The “Eliza–Student” software built upon the developed algorithms is oriented to a fairly broad subject domain, which includes a fair amount of tasks from the Unified State Exam (the Russian abbreviation is “ЕГЭ”, an English analogue is SAT) in informatics. The developed system is able to explain actions performed during the analysis of the text, which contains user questions on solving certain tasks in informatics, solve them and explain decision making in solving process. It seems that the reciprocal form of interaction seems to be the most natural in the learning process. The analysis process is divided into a sequence of stages (preliminary, morphological, syntactic and semantic analysis). Each of them uses different models of language and subject domain. The proposed approach is based on the following ideas: abstraction from the subject area to the latest stages of analysis and focus on the result, i.e. the construction of the most probable, perhaps incomplete, representation of the meaning, despite the incompleteness of the initial information or possible errors in the analysis process. The developed algorithms can be applied to different subject domains.
Keywords: представление знаний, человеко-машинный интерфейс, естественный язык, задачи по информатике, морфологический анализ, синтаксический анализ, семантический анализ, фреймовая модель, модель «смысл–текст», диалог с эвм, текстоориентированный интерфейс, программные системы
Visitors: 332

5. Synergetics of information-cognitive interaction in intelligent robotic systems with remote knowledge exchange [2017-11-28]
Authors: Ulyanov S.V. (ulyanovsv@mail.ru) - Dubna Internacional University for Nature, Socitty and Man, Ph.D Ph.D; A.G. Reshetnikov (reshetnikovag@pochta.ru) - Dubna State University, Institute of the System Analysis and Control, ;
The article describes a technology of knowledge bases remote design for fuzzy controllers, which are developed using the software toolkit “Knowledge base optimizer” based on soft and quantum computing. The paper also considers the possibility of tuning and transferring a knowledge base using remote connection to a controlled object. The presented technologies allow increasing control system robustness by adding training and adapting functions to various management situations.There is a comparison of control quality in fuzzy controllers operating in various control modes. Configuring and transferring fuzzy controller knowledge bases is performed using a remote connection with a control object online via Bluetooth and WiFi. As examples, there are different models of intelligent autonomous robots. Remote transmission of knowledge bases allows designing many different built-in intelligent regulators to implement a variety of control strategies under uncertainty and risk. The implemented technology of knowledge sharing in the group of intelligent robots allows achieving the goal of control and gaining additional knowledge by creating a new information source based on the synergistic effect of combining knowledge. The article considers various options of interaction between robotic systems. There is a brief description of each system. The experimental results demonstrate the possibility of guaranteed achievement of the control goal by a group of robots using soft computing technologies when designing knowledge bases of fuzzy controllers. The developed software toolkit allows designing and configuring complex ill-defined and poorly formalized technical systems online. This feature significantly reduces the time for intelligent control system design and improves system reliability by reducing the level of influence of expert estimates on the design process.
Keywords: knowledge synergetic, remote transmission of knowledge, fuzzy controller, intelligent control, multiagents systems,
Visitors: 484

6. A method for improving interpretability of regression models based on a three-step building cognition model [2017-11-28]
Authors: Kulikovskikh I.M. (kulikovskikh.i@gmail.com) - Samara State Aerospace University, Ph.D Ph.D;
Increasing generalization performance of regression models leads to a more effective solution for the problems of recognition, prediction, and extraction of social and engineering behavior strategies. A number of known methods for improving the generalization properties demonstrate computational effectiveness, hovewer they reduce interpretability of a model and results. This study is an attempt to approach this problem looking at the methods of regression and classification from digital filtering and psychometrics points of view. Considering the advantages of the methods for solving the interpretability problem in these areas, this research is aimed at defining a method to improve the interpretability of regression models by promoting learner’ internal uncertainty in machine learning. In order to solve the problem, the author has developed a three-step model of building cognition. This model reflects direct relations among digital filtering, psychometrics, and machine learning. These research areas employ the same sources of internal uncertainty that makes creating consistent mathematical models that connects the areas possible. For this purpose, the paper considers internal uncertainty from a cognitive point of view as processes of forgetting and guessing. The findings of this study provide the implementations of the following steps in accordance with the tree-step model: a filter synthesis step, a psychological assessment step, and an integrated regression/classification step. While the first step models an engineering environment and the second step presents a social environment, the integrated step helps to create a social-engineering environment. In addition, in contrast to the social environment that may simulate human cognition, the social-engineering environment seems promising in introducing machine cognition. The proposed implementations allow formalizing the method for improving interpretability of regression models changing from one kind of cognition to the other.
Keywords: hegel’s philosophical system, internal uncertainty, psychometrics, digital filtering, machine learning
Visitors: 467

7. Fuzzy data storing and efficient processing in PostgreSQL DBMS [2017-11-28]
Authors: Sorokin V.E. (sorokinve@yandex.ru) - Developed in the Research Institute "CENTERPROGRAMMSYSTEM", Ph.D Ph.D;
In just half a century the theory of fuzzy sets has developed from theoretical foundations to practical use in artificial intelligence systems in such areas as industrial equipment and vehicles control, medical diagnosis and expert systems, including risk assessment, from economic to environmental. Many of them need efficient and reliable storage and processing of large volumes of information. For this purpose, there are DBMS, the most advanced of them are the object-relational DBMS. However, fuzzy data are difficult to reconcile with both object and relational data models. Moreover, the majority of industrial DBMS do not contain built-in fuzzy data types and mechanisms to work with them. These DBMS include cross-platform and freely distributed in source object-relational DBMS called PostgreSQL. Import substitution in infrastructure software is largely associated with application of PostgreSQL. Opportunities of fuzzy data relational modeling and a developed mechanism for extending types through the creation of the required user-defined types along with powerful procedural languages in PostgreSQL allow implementing various alternative approaches to fuzzy data storage and handling. The article shows a comparative analysis of these approaches from the point of view of maintaining data integrity and processing efficiency. There are the experimental results at various fuzzy data models depending on approaches. The paper proposes design solutions that increase the efficiency of fuzzy data search, and formulates recommendations on choosing an approach to modeling fuzzy data.
Keywords: sql query efficiency, data integrity, fuzzy logic operations, database management system, PostgreSQL, database management system, fuzzy set, linguistic variable
Visitors: 552

8. Architecture of an intelligent optimal control system for multi-stage processes evolution in a fuzzy dynamic environment [2017-11-28]
Authors: Palyukh B.V. (pboris@tstu.tver.ru) - Tver State Technical University, Ph.D Ph.D; Vetrov A.N. (vetrov_48@mail.ru) - Tver State Technical University, Ph.D Ph.D; I.A. Egereva (irina.egereva@gmail.com) - Tver State Technical University, Ph.D Ph.D;
The article considers key elements of the approach to creating a system of intellectual information support of innovations at the enterprise. The approach is based on the integration of search mechanisms for innovative solutions and methods of industrial-technological system evolution control using the created store of innovative solutions, algorithms of coordinated optimization and process parameters identification. The paper examines the possibility of using the proposed approach with respect to the base version of the industrial-technological system functioning model. The project is dedicated to a fundamental scientific problem of developing methods and model means of optimal control of multi-step processes evolution under conditions of dynamic uncertainty to enhance their effectiveness and long-term sustainability throughout their life cycle. The authors consider a multistage process as a multi-agent system, its effective management depends on consistent behavior of the center and agents, their interest in finding and implementing innovative solutions, ability to analyze the possibilities of evolutionary development. The approach behind the proposed in the project of a formal apparatus for optimal control of multi-step process evolution includes development and study of a mathematical model of managing multi-stage processes evolution in a fuzzy dynamic environment. It also involves development of a method of solving the problem of managing multi-stage processes evolution in the form of the optimal (suboptimal) control law with feedback and the study of asymptotic properties of solutions for a functional equation obtained for autonomous systems. The project content also includes development of methods for coordinated optimization when the center interacts with agent groups in terms of expanding their production and technological capabilities. Implementation of the developed methods and models involves creating a prototype of an intelligent system for optimum control of a multi-stage processes evolution in a fuzzy dynamic environment.
Keywords: multistage processes, optimal control, evolution managing, information system
Visitors: 539

9. Classification and clustering methods for improving efficiency of case-based systems [2017-11-28]
Authors: Varshavskiy P.R. (VarshavskyPR@mpei.ru) - National Research University “MPEI”, Ph.D Ph.D; Ar Kar Myo (arkar2011@gmail.com) - National Research University “MPEI”, ; D.V. Shunkevich (shunkevichdv@gmail.com) - Belarusian State University of Informatics and Radioelectronics (BSUIR) ;
The article examines topical issues of improving efficiency of case-based reasoning (CBR) systems. Case-based methods and systems (CBR systems) are actively used to solve a number of problems in the field of artificial intelligence (for example, for modeling plausible reasoning (common sense reasoning), machine learning, intellectual decision support, intelligent information search, data mining (DM) and etc.). It should be noted that modern tools for DM, which are widely used in intelligent systems, database and knowledgebase management systems, business ap-plications, machine learning systems, electronic document management systems, etc., do not have advanced CBR tools. The paper proposes to use the modified CBR cycle to increase the efficiency of CBR systems. This cycle allows creating a base of successful (CB) and unsuccessful cases (UCB) based on available expert information (test samples), as well as the k-nearest neighbors (k-NN) modification algorithm for case retrieval. The proposed modifications allow improving the quality of solving DM tasks (in particular, data classification task). In addition, the authors consider the possibility of reducing the number of cases in CB using classification and clustering methods to improve performance of CBR systems. The paper shows computational experiments to estimate the effectiveness of the solutions offered while working on a data set from the UCI Machine Learning Repository. They use CBR system prototype developed in MS Visual Studio in C# language.
Keywords: clusterization, classification, data intelligent analysis, case-based approach, intellectual system
Visitors: 580

10. Cognitive hybrid systems for decision support and forecasting [2017-11-28]
Authors: A.N. Averkin (averkin2003@inbox.ru) - Dubna International University for Nature, Society and Man, Ph.D Ph.D; Yarushev S.A. (sergey.yarushev@icloud.com) - Dubna International University for Nature, Society and Man, ; V.Yu. Pavlov (averkin2003@inbox.ru ) - Moscow Aviation Institute (National Research University), Ph.D Ph.D;
The paper considers a number of models for decision-making support in dynamic situations that are characterized by weak structuring based on a hybrid system integrating a fuzzy hierarchical assessment model and a fuzzy cognitive situation model. The paper presents a hybrid model based on cognitive maps and Saati decision support hierarchies in dynamic situations and a fuzzy production model for modeling people's irrational behavior in the problems of behavioral economics. When creating a behavioral decision-making model, we were taking into account the modules responsible for decision maker’s emotions and internal model representativeness. The model uses fuzzy logic and production rules. This approach makes the decision-making model intuitive due to linguistic variables that form production rules. Another advantage is universality and scalability obtained when switching to models with a large number of parameters. The paper presents a model of a modular time series forecasting system. It consists of modules based on modular neural networks, a module that includes a fuzzy cognitive map hybrid and a neural-fuzzy ANFIS network and modules for verifying and aggregating the results. This article considers in detail a module combining a fuzzy cognitive map and a neural-fuzzy network. There is the constructed neural network and its structure is shown in combination with a fuzzy cognitive map based on the forecast of the indicator “living standards”. Business analytics systems use similar approaches for knowledge economics based on intelligent decision support systems that use cognitive methods of analyzing consciousness of people involved in these processes, as well as testing decision makers’ quality by their brain activity, for parametric adjustment of intelligent systems decision support.
Keywords: forecasting, neural network, cognitive maps, fuzzy systems, fuzzy-neural networks, decision support, hybrid models
Visitors: 612

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