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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology

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issn 2310-6018

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metadata of articles for the last 2 years

Review of neural network models for solving the problems of predicting emergency situations and ensuring the safe operation of oil and gas wells

2024. T.12. № 1. id 1472

Sulavko A.E. Vasilyev V.I. Klinovenko S.A. Lozhnikov P.S. Suvyrin G.A. Guzairov M.B.

DOI: 10.26102/2310-6018/2024.44.1.017

An analytical study was carried out on the problem of preventing emergency situations and predictive diagnostics of equipment during hydrocarbon production in oil and gas fields as well as the ways to solve this problem by means of artificial intelligence based on deep neural networks. One of the key factors hindering the development of predictive equipment diagnostic systems is the lack of data describing pre-emergency situations, which is necessary for high-quality training of neural network models. An analysis of recent publications and research on the subject of telemetry data analysis and emergency recognition is provided. Neural network models are considered that can be used to predict the failure of pumping and compressor equipment and other units. Cases of the use of neural network models specially trained to solve this problem, as well as neural network models used in other tasks but analyzing similar data structures, were studied. The issue of transfer learning is raised to adapt neural network models originally developed and trained for other areas to use in the area under consideration in order to reduce the sample size when training industrial artificial intelligence. A comparison of the achieved results was carried out, and the advantages and disadvantages of existing technical solutions were identified.

Keywords: artificial neural networks, predictive diagnostics, machine learning, time series, telemetry, maintenance, data sets

Dysarthria speech recognition by phonemes using hidden Markov models

2024. T.12. № 1. id 1471

Bredikhin B.A. Antor M. Khlebnikov N.A. Melnikov A.V. Bachurin M.V.

DOI: 10.26102/2310-6018/2024.44.1.002

The relevance of the paper is due to the difficulties of oral interaction between people with speech disorders and normotypic interlocutors as well as the low quality of abnormal speech recognition by standard speech recognition systems and the inability to create a system capable of processing any speech disorders. In this regard, this article is aimed at developing a method for automatic recognition of dysarthric speech using a pre-trained neural network for recognizing phonemes and hidden Markov models for converting phonemes into text and subsequent correction of recognition results using a search in the space of acceptable words of the nearest Levenshtein word and a dynamic algorithm for splitting the output of the model into separate words. The main advantage of using hidden Markov models in comparison with neural networks is the small size of the training data set collected individually for each user, as well as the ease of training the model further in case of progressive speech disorders. The data set for model training is described, and recommendations for collecting and marking data for model training are given. The effectiveness of the proposed method is tested on an individual data set recorded by a person with dysarthria; the recognition quality is compared with neural network models trained on the data set used. The materials of the article are of practical value for creating an augmented communication system for people with speech disorders.

Keywords: hidden Markov models, dysarthria, automatic speech recognition, phonemes recognition, phoneme correction

Development of hybrid atmospheric-underwater optical communication system

2024. T.12. № 1. id 1468

Ali M. Saklakov V.M.

DOI: 10.26102/2310-6018/2024.44.1.032

Underwater optical wireless communications are promising and future-oriented wireless carriers to support underwater activities focused on 5G and beyond (5GB) wireless systems. The main challenges for the deployment of underwater applications are the physicochemical properties and strong turbulence in the transmission channel. Therefore, this paper analyzes the end-to-end performance of a hybrid free space optics (FSO) and underwater wireless visible light communication (UVLC) system under intensity modulation or direct detection (IM/DD) in a method considering a pulse amplitude modulation (PAM) scheme. In this study, a fading model with Gamma-Gamma (GG) distribution is used to deal with channel conditions with moderate and strong turbulence, and the links are designed by combining plane wave modeling in the corresponding links, respectively. The proposed performance methods excel in higher achievable data rates with minimal delay response and improves network connectivity in real-time monitoring scenarios compared to conventional underwater wireless communication techniques. The simulation results provide reliable estimates of system performance metrics such as average bit error rate (ABER) and probability of failure (Pout) in the presence of pointing errors. Finally, this paper uses a Monte Carlo approach for best curve fitting and validate the numerical expression with simulation results.

Keywords: 5G and 5GB networks, cooperative communication, optical communication, underwater communication, underwater sensor networks (USNs), VLC light communication

Functional near-infrared spectroscopy (fNIRS) as a hybrid system: a review

2024. T.12. № 1. id 1459

Samandari A.M.

DOI: 10.26102/2310-6018/2024.44.1.005

Sensor devices and biomedical imaging technologies used in clinical application scenarios are essential for providing a comprehensive portrait of patients’ state, but these technologies, despite their outstanding advantages, have their inherent disadvantages. Beginning with the principle of complementary images of medical imaging techniques, this review examines the functional near- infrared spectroscopy (fNIRS) technique and its use as a hybrid system. The fNIRS technology delivers impressive results in terms of the biological signal classification accuracy, but its use as a hybrid system with electroencephalography (EEG) and electromyography (EMG) achieved better results because it has become a complementary tool to fill the deficit of the common technology with it, and this has been highlighted in this review. The results show that the superiority in the biological signal classification accuracy provided by hybrid systems from fNIRS with EEG and EMG would provide a comprehensive and objective assessment of the patients’ state from the stage of illness to healing. In conclusion, we have no indication from the scientific studies of the previous four years (2020–2023) that demonstrate which of the hybrid systems is better than others when used in clinical practice, and this encourages further in-depth studies to validate the combination of methods to prove their success and preference.

Keywords: HBCIs, fNIRS, fMRI, EEG, EMG, MEG

Finite element modeling of thermohydraulic processes by the porous body method

2024. T.12. № 1. id 1457

Yaurov S.V. Danilov A.D. Gusev K.Y.

DOI: 10.26102/2310-6018/2024.44.1.006

The paper considers the best-known models of a porous body used to simplify the performance of thermohydraulic calculations by the finite element method. The main approaches and dependencies when using the porous body model in calculations are shown. The results of thermohydraulic calculations using the Darcy porous body model are presented. The calculation of a heat exchanger with spirally wound tubes was performed, the calculation of a complex technological system consisting of mechanical filters of different configurations was performed. The discrepancies between the calculated and actual parameters of the equipment are determined. The use of a porous body model as a hydraulic analogue of equipment using the example of mechanical filters and a heat exchanger showed acceptable results (deviations from the design values range from 0,1 % to 10 %). These discrepancies are related to the accuracy/correctness of the selection of porous body resistance laws (dependencies). The use of the porous body approach in modeling the operating modes of technological systems including equipment with a complex design is explained, first of all, when it is required to predict the operating modes of the system as a whole from the result of computational modeling, but local processes occurring inside the equipment are not. Secondly, when it is necessary to reduce the time for performing calculations with low available power capabilities of computers. However, the proposed approach has disadvantages, in particular, the procedure for determining the degree of porosity of the simulated object and the laws of hydraulic resistance selected from empirical dependencies is quite complex.

Keywords: porous body model, complex technological systems, heat exchanger, finite element method, hydraulic resistance, mechanical filters

Automated generation of a complete data model of production facilities in a unified information environment

2024. T.12. № 1. id 1456

Filimonova A.A. Chizhov M.I. Vetokhin V.V. Sobenina O.V.

DOI: 10.26102/2310-6018/2024.44.1.003

The article examines the problem of developing an integration platform to facilitate end-to-end business processes supporting the life cycle of heterogeneous information objects. The platform topology is chosen according to the functionality of the integrated systems and the structure of the information object. To create a unified enterprise information environment, various topologies are considered, including peer-to-peer, message broker, centralized, and hybrid topologies. The basis for the description of an object is a complete data model, including defining attributes and transformation rules corresponding to each of the integrated systems. Using the object model of the information support system for digital products and special templates, a methodology for forming policies, methods and documents (PMD) and organizing a unified digital environment of the enterprise is proposed. However, to solve this problem, the development of a specialized integration platform is required which is capable of processing data from production facilities on a centralized basis and facilitating their interaction in a unified information environment. Such a platform must take into account the characteristics of each system component and ensure the security of information exchange; it also should be able to scale and adapt to the changing needs of the enterprise. In addition, this article discusses in detail various topologies for creating a unified enterprise information space. Peer-to-peer, message brokered, centralized, and hybrid topologies are included. Each of these topologies has its own characteristics and advantages, and the choice of the optimal one depends on the requirements and characteristics of a particular enterprise. To successfully implement integration and create a unified digital environment of the enterprise, it is suggested to use an object model of an information support system for digital products. This model helps to structure information and determine the relationships between various components of the system. Furthermore, the article proposes a methodology for the formation of PMD, which is the basis for organizing a unified digital environment of the enterprise. This methodology takes into account the requirements for security, consistency and efficiency of the system and also ensures standardization and consistency of processes within the enterprise.

Keywords: information production facilities, integration, digital environment, full data model, process automation

Optimization of modeling processes of balancing and rebalancing investments for the implementation of multi-object organizational system development program

2024. T.12. № 1. id 1419

Bukholtsev I.M. Lvovich Y.E.

DOI: 10.26102/2310-6018/2024.44.1.015

The article examines the optimization of investment management in the formation and implementation of multi-object information system development program. The stage connected with the transition from the development program executed for a certain time period to a new development program with a given planning horizon is considered. It is shown that the investments are balanced at the moment of transition and the need to rebalance them arises in the process of implementation. For the first problem, a multilevel system of balance conditions is formed, which is the basis for the construction of optimization models of the balancing process. Since the lower level of balance conditions is associated with the requirement to increase the value of organizational system development indicators of objects up to a certain value set by the managing center, the optimization problems are based on predictive assessments. These estimates are calculated either using the results of neural network modeling or expert evaluation. When forming optimization models of the investment rebalancing process, two ways of detecting the deviation of the development indicators value from the planned growth trajectory are considered: at a given point in time; when the threshold value is exceeded. In these cases, the point in time is determined, at which the optimal strategy of investment allocation between time transitions is adjusted in order to reach a given level of development indicators at the end point. Thus, the proposed transition makes it possible to optimize the distribution of investments as part of the development program both in the process of their balancing and rebalancing.

Keywords: multi-object organization system, development program, investment, optimization, neural-network modeling, expert assessment

Metrics of semantic proximity of a user's request as a security criterion in a thematic hierarchical access control model

2024. T.12. № 1. id 1382

Khvostov V.A. Sych G.V. Choporov O.N. Gulov V.P.

DOI: 10.26102/2310-6018/2024.44.1.030

The increasing scope of application of mobile technologies and devices as elements of distributed systems to enhance the efficiency and convenience of access to various information systems and digital services has made it necessary to improve methods and mechanisms for information protection and information security. One of the main security mechanisms is access control. Features of traditional (discretionary and mandatory) access control model application in distributed information systems (IS) when using mobile systems (MS) as elements are analyzed. Thematically, hierarchical model is proposed as the most effective model that meets the required security policy. For this access control model, an ontological method for forming trust rights to access objects is proposed based on the use of semantic proximity metrics. When using traditional thematic hierarchical access control models, the logical information architecture of IS resources forms a thematic hierarchical classifier (categorizer). The Hasse diagram introduces order relations in the thematic classifier on the security grid to form trust-thematic powers of IS users. Constructing Hasse diagrams on a security grid that includes several security levels is a rather complex algorithmic task. When constructing trust-thematic powers of users in order to avoid uncertainty due to the incompleteness of the constructed Hasse diagram and overestimation of the granted powers when forming access rights, it is proposed to use the semantic proximity of the user access request and the thematic heading of the hierarchical classifier. An analysis of existing approaches to the formation of semantic proximity metrics has shown that proximity measures based on the hierarchy of concepts can be used as the best metric for setting the user’s trust authority.

Keywords: mobile station, access control, hierarchical thematic classification, semantic proximity, semantic distance