Computer Expert System Research Articles

Computational ensemble expert system classification for the recognition of bruxism using physiological signals

This study aimed to develop an automatic diagnostic scheme for bruxism, a sleep-related disorder characterized by teeth grinding and clenching. The aim was to improve on existing methods, which have been proven to be inefficient and challenging. We utilized a novel hybrid machine learning classifier, facilitated by the Weka tool, to diagnose bruxism from biological signals. The study processed and examined these biological signals by calculating the power spectral density. Data were categorized into normal or bruxism categories based on the EEG channel (C4-A1), and the sleeping phases were classified into wake (w) and rapid eye movement (REM) stages using the ECG channel (ECG1-ECG2). The classification resulted in a maximum specificity of 93% and an accuracy of 95% for the EEG-based diagnosis. The ECG-based classification yielded a supreme specificity of 87% and an accuracy of 96%. Furthermore, combining these phases using the EMG channel (EMG1-EMG2) achieved the highest specificity of 95% and accuracy of 98%. The ensemble Weka tool combined all three physiological signals EMG, ECG, and EEG, to classify the sleep stages and subjects. This integration increased the specificity and accuracy to 97% and 99%, respectively. This indicates that a more precise bruxism diagnosis can be obtained by including all three biological signals. The proposed method significantly improves bruxism diagnosis accuracy, potentially enhancing automatic home monitoring systems for this disorder. Future studies may expand this work by applying it to patients for practical use.

An approach to logical-mathematical computer modeling of linear and nonlinear dynamical systems

The paper deals with the problem of modeling linear and nonlinear dynamical systems using information technologies and programming. The processes of modeling, synthesis and inference of solutions to problems are considered, and the possibility of their integration within the described approach is shown. The substantive aspects of the development of special mathematical and algorithmic support for the construction of a software system for the analysis and processing of expert information for the purposes of automated synthesis and inference of solutions are briefly outlined. The aim of the work is to create a new approach of logical-mathematical computer modeling of linear and nonlinear dynamical systems and to develop a prototype of a software computational expert system based on it. As a result of the research, a universal approach of logical-mathematical computer modeling of linear and nonlinear dynamical systems has been developed and proposed. The proposed approach can be used to organize the process of computer modeling and automated synthesis of task solutions with the output of their results. The mathematical model of the knowledge base and process of its construction for the selected subject area, as well as the algorithm for outputting solutions to problems with its software implementation in the Python programming language, are shown. Examples of solution output for various linear and nonlinear problems are given. The developed prototype of the software computational expert system using the proposed logical- mathematical approach will significantly simplify the process of modeling dynamical systems and make the solution of problems' simpler and more understandable.

Expert Systems in HRM : A Digital Construction

The main objective of this research is to carefully describe the role of Expert Systems (ES) in human resource management discourse. What logical constructs must be built when there is a desire to empower the capabilities of computational expert systems in their pragmatic use. Human Resource Expert Systems (HRES) can mimic the decision-making capabilities of a Human Resource Expert (HRE). The design and development of HRES depends on top management initiative and support. The implementation of HRES should be holistic, with maximum participation from all departments in the organization. This study uses a qualitative descriptive method, with a literature study approach. The main data is drawn from a variety of selected journal papers, taken from reputable journals. Other sources that are compatible with the research, such as news, academic papers, videos and other documents. The study found that there is a challenge to reduce the fear of computers in HR functions and resistance to change. HRES can increase productivity levels by assisting HR managers in making rational decisions to solve unstructured HR related problems. The emphasis is on organizational change and bold initiatives to further implement ES in the HR domain and overcome challenges. This paper aims to analyse the focus areas of HRES and the functions where HRES faces limitations and challenges.

The relative role of polar and nonpolar factors of the structure of substance on the process of their penetration through the blood–brain barrier

The analysis of the relative role of polar and non-polar factors of the molecular structure on the penetration of substances through the blood–brain barrier (BBB) was carried out. Such analysis will allow a preliminary approximate assessment of the ability of substances to cross the blood–brain barrier. Using previously developed computer expert systems on the basis of QSAR/QSPR models in the framework of simplex approach, the water solubility logSw (polar factor model), the lipophilicity logP (nonpolar factor model), and the characteristics of penetration through the blood–brain barrier (logBB, logPS, logP0PAMPA–BBB) were calculated for a set of 614 different organic compounds. It was determined whether substances belong to classes BBB+ or BBB– and whether these substances are substrates of P-glycoprotein (P-gl) or not (no-P-gl). Analysis of the distribution of the points of the investigated molecules in the logP vs. logSw coordinates revealed that lipophilicity and water solubility for the compounds with high penetrating ability should be approximately in following ranges: 3logP6; and –5logSw–1. For the data, which are presented in different scales, continuous scale and classification scale, a half-sign correlation coefficient Rss was calculated. Rss equals 0.93, that confirms the consistency of the results of the prognosis of Log BB parameters and classification BBB+/BBB–. The general trends in the classification of the investigated compounds according to the BBB+/BBB– and P-gl/no-P-gl classes were quantitatively estimated. The sign coefficient of association, which equals –0.35, emphasizes the antibatic nature of the relationship between the data of the two classifications.

Using computer expert system to solve complications primarily due to low and excessive birth weights at delivery: Strategies to reviving the ageing and diminishing population

The world now lives in an ageing society. Significant empirical evidence from the literature revealed that the world’s total fertility rate (TFR) estimate has experienced a declining trend from 5.30 in 1963 to 2.3 in 2020. The TFR for 2023 for the United States was 1.84, Canada 1.57, United Kingdom 1.63, Germany 1.58, Japan 1.39, China 1.45, Nigeria 4.57, India 2.07, Ghana 3.61, with Taiwan 1.09 and Niger 6.73 having the least and highest respectively. Non-adherence to God's childbearing principles, a female's age when she has her first child, educational opportunities, access to family planning, and government acts and policies affecting childbearing are all factors that may influence TFR. Despite the danger posed by the declining TFR trend, childbearing challenges and complications primarily due to low and excessive birth weights at delivery have heightened this danger. This study highlights strategies to leverage the provision of a computerized expert system (ES) solution to the problems of complications primarily due to low and excessive birth weights at delivery. A Knowledge-Based System (KBS) framework to simulate the problem-solving behavior of an expert in a narrow domain or discipline to unite the accumulated expertise of individual disciplines such as gynecology, ultrasonography, computer software design, and engineering was adopted. Fetal weight has been found to be a function of fetal head circumference (HC), femur length (FL), abdominal circumference (AC), and biparietal diameter (BPD) and predictable with a polynomial equation. Also, fetal age has been found to be a function of fetal weight and predictable by an equation. The equations for the determination of conception date and delivery dates were derived. The Expert System (ES) primarily estimates fetal parameters (fetal weight, fetal age or gestational age, conception date, and delivery date) in the first trimester using ultrasonographic fetal biometric data. The result of this study may eliminate or reduce the occurrence of potential complications associated with the birth of both small and excessively large fetuses, thereby contributing to reviving the world declining population.

ВИКОРИСТАННЯ ПАКЕТІВ МОДЕЛЮВАННЯ СИСТЕМНОЇ ДИНАМІКИ УПРАВЛІННЯ ЗАПАСАМИ В ВИРОБНИЧО-ТОРГОВИХ ОРГАНІЗАЦІЯХ, ЯКІ ПОСТАВЛЯЮТЬ МАТЕРІАЛЬНО-ТЕХНІЧНІ ЗАСОБИ ДЛЯ ЗБРОЙНИХ СИЛ УКРАЇНИ

Planning of difficult logistic structures is presently conducted with the use of the special software products and modern information technologies. Presently in this area of widest find various computer expert facilities and systems of planning of processes of logistic. Large possibilities in this area are possessed by the packages of structural design. They allow not only to prepare the proper recommendations and projects on the base of exact analytical methods but also give them an evident, visual form. In this article the considered approaches of design of system dynamics of control of inventories in production-point-of-sale organizations which supply, material and technical facilities for Military Powers of Ukraine. The example of visual model of logistic chain is described developed at to the environment of package of structural design of iThink It is marked that work with the package of iThink does not require the special skills and knowledge of programming language. A model is developed by placing in a graphics editor separate component and them subsequent connection. If necessary intercommunications are set between separate knots. Analysing the package of structural design it is possible to draw a conclusion, that facilities of structural design of are some hard limits on the process of design. A model can be developed practically for any system of financial streams and supplies any the organizations of any pattern of ownership. Also it should be noted that design of activity of economic subjects exceptionally effective and perspective direction of development of administrative technologies. World experience testifies that computer analysis of the logistic systems, a condition is needed for the effective planning of creation and management similar difficult organizations Keywords: logistic system, system of logistical support of Military Powers of Ukraine, production-point-of-sale organizations, structural design.

AI-Based Computer Vision Techniques and Expert Systems

Computer vision is a branch of computer science that studies how computers can ‘see’. It is a field that provides significant value for advancements in academia and artificial intelligence by processing images captured with a camera. In other words, the purpose of computer vision is to impart computers with the functions of human eyes and realise ‘vision’ among computers. Deep learning is a method of realising computer vision using image recognition and object detection technologies. Since its emergence, computer vision has evolved rapidly with the development of deep learning and has significantly improved image recognition accuracy. Moreover, an expert system can imitate and reproduce the flow of reasoning and decision making executed in human experts’ brains to derive optimal solutions. Machine learning, including deep learning, has made it possible to ‘acquire the tacit knowledge of experts’, which was not previously achievable with conventional expert systems. Machine learning ‘systematises tacit knowledge’ based on big data and measures phenomena from multiple angles and in large quantities. In this review, we discuss some knowledge-based computer vision techniques that employ deep learning.

Universalization of conceptual modeling for crisis management in road enterprises based on object-oriented approach

The article is devoted to the problem of taking into account different types of similarities in the conceptual models of enterprises, which is advisable when creating computer expert systems, in particular, those intended for crisis management. This is necessary in order to exclude reworking of the conceptual model components from the very beginning. Models and theories of crisis management are the basis for its further conceptual modeling. To develop them, it is advisable to use the so-called object-oriented approach, which makes it possible not to develop certain parts of the conceptual model each time, but to reuse them without any changes. This reduces the labor intensity, shortens the time required to create a conceptual model and improves its quality.

Analysis of Home Appliances Functional Failure on Certainty Factor-Based Engineering ACS

Technological developments are currently experiencing very rapid changes along with human needs that are increasingly numerous and complex. Not only in the fields of health, education, agriculture, and so forth. However, the electronics industry has also been affected by the development of this technology. The production of household electronic devices or home appliances that combine sophistication of technology and modern designs has emerged and is much in demand by the public, one of which is the refrigerator. Even with the development of this technology, it does not mean that the refrigerator can function properly forever if it is used continuously. Because the refrigerator requires maintenance and repair if there is damage. In diagnosing damage to a 2-door no frost home appliances refrigerator, limitations in information, knowledge, and experience from the public and technicians cause delays in recognizing the damage that has occurred, which also affects decision-making in handling it. Then a system will be formed using an expert system computer program with the Certainty Factor method. The Certainty Factor method is a method for accommodating statements from an expert in their delivery. where a website-based expert system is created that can be used without any space and time limitations to help new technicians and the public. The result of testing this method is the resulting accuracy rate of more than 90% of the data
 has been tested so that it can assist technicians in diagnosing damage to the no frost 2 door refrigerator

An artifiсial intelligence computer system for differential diagnosis of lysosomal storage diseases

Aim. To improve the efficiency of diagnosis of hereditary lysosomal storage diseases using an intelligent computerbased decision support system.Materials and methods. Descriptions of 35 clinical cases from the literature and depersonalized data of 52 patients from electronic health records were used as material for clinical testing of the computer diagnostic system. Knowledge engineering techniques have been used to extract, structure, and formalize knowledge from texts and experts. Literary sources included online databases and publications (in Russian and English). On this basis, for each clinical form of lysosomal diseases, textological cards were created, the information in which was corrected by experts. Then matrices were formed, including certainty factors (coefficients) for the manifestation, severity, and relevance of signs for each age group (up to 1 year, from 1 to 3 years inclusive, from 4 to 6 years inclusive, 7 years and older). The knowledge base of the expert system was implemented on the ontology network and included a disease model with reference variants of clinical forms. Decision making was carried out using production rules.Results. The expert computer system was developed to support clinical decision-making at the pre-laboratory stage of differential diagnosis of lysosomal storage diseases. The result of its operation was a ranked list of hypotheses, reflecting the degree of their compliance with reference descriptions of clinical disease forms in the knowledge base. Clinical testing was carried out on cases from literary sources and patient data from electronic health records. The criterion for assessing the effectiveness of disease recognition was inclusion of the verified diagnosis in the list of five hypotheses generated by the system. Based on the testing results, the accuracy was 87.4%.Conclusion. The expert system for the diagnosis of hereditary diseases has shown fairly high efficiency at the stage of compiling a differential diagnosis list at the pre-laboratory stage, which allows us to speak about the possibility of its use in clinical practice.

Machine learning models effectively distinguish attention-deficit/hyperactivity disorder using event-related potentials

Accurate diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD) is a significant challenge. Misdiagnosis has significant negative medical side effects. Due to the complex nature of this disorder, there is no computational expert system for diagnosis. Recently, automatic diagnosis of ADHD by machine learning analysis of brain signals has received an increased attention. This paper aimed to achieve an accurate model to discriminate between ADHD patients and healthy controls by pattern discovery. Event-Related Potentials (ERP) data were collected from ADHD patients and healthy controls. After pre-processing, ERP signals were decomposed and features were calculated for different frequency bands. The classification was carried out based on each feature using seven machine learning algorithms. Important features were then selected and combined. To find specific patterns for each model, the classification was repeated using the proposed patterns. Results indicated that the combination of complementary features can significantly improve the performance of the predictive models. The newly developed features, defined based on band power, were able to provide the best classification using the Generalized Linear Model, Logistic Regression, and Deep Learning with the average accuracy and Receiver operating characteristic curve > %99.85 and > 0.999, respectively. High and low frequencies (Beta, Delta) performed better than the mid, frequencies in the discrimination of ADHD from control. Altogether, this study developed a machine learning expert system that minimises misdiagnosis of ADHD and is beneficial for the evaluation of treatment efficacy.Graphical abstract

Fifty years of experience in rate of penetration management: Managed pressure drilling technology, mechanical specific energy concept, bit management approach and expert systems - A review

Rate of penetration (ROP) management is a matter of great importance in drilling operations, therefore it has been considered in different field management projects and research studies. In this way, several drilling technologies and concepts such as managed pressure drilling (MPD) and mechanical specific energy (MSE) have found their applications in this category. Moreover, some studies have used the bit management approach, while some other authors have developed special computer software and expert systems for this purpose. The history of ROP management studies reaches to more than half a century. In this article, some of these studies are reviewed to achieve a better understanding of this concept, its economic benefits and also its research capacities. Results indicate that among different methods which are discussed in this paper, bit management have the most field applications in ROP management studies.

Randomized Trial of a Physical Activity Intervention for Latino Men: Activo

Latino men experience disproportionately high rates of diseases related to low physical activity, yet they are poorly represented in physical activity intervention trials. Efforts to promote physical activity in Latina women show promising results, yet such interventions are yet to be extended to Latino men. This study tested a computer expert system‒tailored, text messaging-supported physical activity intervention for underactive Spanish-speaking Latino men compared with a control group matched for contact time. Potential predictors of intervention success were also explored. Randomized trial. Participants were randomized to receive a Tailored Physical Activity Intervention (Intervention) or a Wellness Control (Control). Data were collected in 2015-2017 and analyzed in 2018-2019. Insufficiently active Latino men (n=46). Intervention participants received a baseline counseling session and then, individually tailored print materials and text messages on a tapered schedule for 6 months. Control participants received printed wellness materials and text messages on the same schedule. Primary outcome was a change in weekly moderate to vigorous physical activity from baseline to 6 months measured by accelerometers. Self-reported moderate to vigorous physical activity measured by the 7-day Physical Activity Recall Interview was a secondary outcome. For Intervention participants, median accelerometer-measured moderate to vigorous physical activity increased from 10.0 minutes/week at baseline to 57.5 minutes/week at 6 months, whereas for Control participants, it increased from 21.0 minutes/week at baseline to 23.0 minutes/week at 6 months (p<0.05). Similar results were found for self-reported moderate to vigorous physical activity. At 6 months, 47% of Intervention participants met national guidelines of 150 minutes/week versus 25% of Control participants (p=0.15, not significant). Findings suggest that an individually tailored intervention can successfully increase moderate to vigorous physical activity in underactive Latino men. Such technology-supported interventions have the potential for broad dissemination. This study is registered at www.clinicaltrials.gov NCT02512419.

Anterior Cruciate Ligament Knee Injury Detection of Sports Persons using Machine Learning Techniques

ACL is one of most common knee injury in sports person which increases as the participation in sports increases. People participating in basketball, football, hockey and athletics generally faces more weight bearing on hip, knee and ankle which is directly breaking of muscular tissues of ACL. After this it is mandatory to rehabilitate and back to the field for sport person at same pre-injury stage. But it requires mental and physical strength to recover from ACL tear and proper treatment needs health management. In a growing age of Information Technology the use of computer and its applications are extensively used in almost all areas. The main objective of this paper is to check the use of expert system or the use of any computerized equipment while diagnosis Anterior Cruciate Ligament injury. There are many techniques and machines to predict the knee injury grade like MRI but to check the accuracy level computer expert system Machine learning techniques are best for the results.

Knowledge base for wind farm devices in the computer expert system

The article presents the issue of determining diagnostic information for the needs of testing the condition of wind farm equipment. To this end, the essence of the structure of an intelligent expert system was presented and described. The structure of the tested object is shown in the form of a functional and diagnostic model. Based on the developed model of the examined object, diagnostic information was determined in the form of a set of basic elements and a set of diagnostic signals, which are later used in the construction of an expert knowledge base. The expert knowledge base is determined by sets of facts and rules applied. An important part of this article is description of the structure of the expert system and the expert knowledge base used in it. Keywords: wind farm, renewable energy, technical diagnostics, diagnostic inference, artificial intelligence

THE USE OF PACKAGES OF DESIGN OF SYSTEM DYNAMICS OF CONTROL OF INVENTORIES IS IN PRODUCTION-POINT-OF-SALE ORGANIZATIONS OF SUPPLYING WITH MATERIAL AND TECHNICAL FACILITIES FOR MILITARY POWERS OF UKRAINE

Planning of difficult logistic structures is presently conducted with the use of the special software products and modern information technologies. Presently in this area of widest преминения find various computer expert facilities and systems of planning of processes of logistic. Large possibilities in this area are possessed by the packages of structural design. They allow not only to prepare the proper recommendations and projects on the base of exact analytical methods but also give them an evident, visual form. In this article the considered approaches of design of system dynamics of control of inventories in production-point-of-sale organizations which supply, material and technical facilities for Military Powers of Ukraine. The example of visual model of logistic chain is described developed at to the environment of package of structural design of iThink It is marked that work with the package of iThink does not require the special skills and knowledge of programming language. A model is developed by placing in a graphics editor separate component and them subsequent connection. If necessary intercommunications are set between separate knots. Analysing the расмотреный package of structural design it is possible to draw a conclusion, that facilities of structural design of ненавязывают are some hard limits on the process of design. A model can be developed practically for any system of financial streams and supplies any the organizations of any pattern of ownership. Also it should be noted that design of activity of economic subjects exceptionally effective and perspective direction of development of administrative technologies. World experience testifies that computer analysis of the logistic systems, a condition is needed for the effective planning of creation and management similar difficult organizations.

The basic areas of research and actual developments of the rolling department of the Institute of Ferrous Metallurgy, Ukraine’ National Academy of sciences

In 1948 in the Institute of Ferrous Metallurgy, a department was created, the basic task of which was the perfection of equipment and technologies of rolling production. Basic research and development activity in the area of sheet and long products production, aimed at elaboration of scientific and technological fundamentals, creation of new and perfection of existing processes of continuous rolling, optimization of rolling processes and management the rolled products quality considered. The most important research and technical development of the department noted, including innovation technologies of rolled products production, expert computer systems for engineer calculations and optimization of the processes parameters, as well as systems of automatic process control. Among the basic areas of research and development achievements, the elaboration of computer simulation of hot-rolled and cold-rolled strip production processes, rebar, wire rod and profiles of high accuracy for machine-building highlighted, as well as predicting of rolled products quality indices, perfection of their production technology. The comprehensive systems elaborated and implemented at the ferrous metallurgy plants aimed at vibro-diagnostic and automatic control of speed of high-speed cold-rolling mills, automatic control of cold-rolled strip flatness, automatic alignment of plate heads, designing of rational configuration of strip mills rolls cooling collectors and prediction of working rolls temperature at their operation. In the area of long products production theoretical fundamental of the continuous long products rolling processes at using non-driven working stands and non-driven dividing facilities elaborated. Fundamental studies of regularity of temperature, deformation and energy-power parameters variation of high-speed continuous rolling process of wire rod at application of reducing-sizing blocks elaborated. The basic approaches to bands and precise profiles of small gauges by rolling-drawing method production efficiency elaborated theoretically and experimentally. A method of determination of rational structure schemes and production parameters of hot-rolled product production from continuously casted billets in the casting-rolling complexes elaborated.

EARLY DIAGNOSIS OF MUSCULAR-JOINT DYSFUNCTION OF THE TMJ WITH THE HELP OF A COMPUTER ADDITIONAL PROGRAM

&#x0D; &#x0D; &#x0D; A topical issue of modern dentistry is the timely diagnosis and treatment of musculoskeletal syndrome of the temporomandibular joint (TMJ). A large number of publications in domestic and foreign literature is devoted to the study of this problem, but there is no single approach to diagnosis and a clear method of examination of the patient to establish a diagnosis. The purpose of our study was to implement a comprehensive methodology for early diagnosis of dysfunction by applying an analysis of a computer expert application we created. Based on the conducted research, in order to synchronize the data, simplify the work and deepen the analysis of diagnostics, an expert computer system for the diagnosis of dysfunction of the TMJ «PR» was developed. The program is applied and has 486 qualitative and quantitative components of the analysis criteria in its analytical base. The necessary parameters of the analysis include: frequency and intensity of headache, unilateral tinnitus, feeling of fatigue of chewing muscles during chewing solid food, degree of mouth opening, nature of movement of the mandible when opening the mouth, results of physical examination methods, the presence of clicks in the TMJ with taking into account the phase of mouth opening etc. s well as quantitative parameters of these additional methods of investigation of infrared thermography of the chewing muscles and area of the TMJ, EMG of chewing and mimic muscles, axiography, MRI, CT, ultrasound, digital analysis of occlusal ratios. The expert system program developed took into account all the maximum possible values of each parameter. The diagnosis was based on a combination of parameter values. The use of the multi-link expert computer system «PR» made it possible to take into account all the parameters of the patient examination and to obtain the most reliable diagnosis, which is necessary both at the initial stage of the patient’s treatment, and for correlation and correction of medical measures in such patients.&#x0D; &#x0D; &#x0D;

Improving the safety of atrial fibrillation monitoring systems through human verification

In this paper we propose a hybrid decision-making process for medical diagnosis. The hypothesis tested is that a deep learning system can provide real-time monitoring of Atrial Fibrillation (AF), a prevalent heart arrhythmia, and a human cardiologist will then verify the results and reach a diagnosis. The verification step adds the necessary checks and balances to increase the safety of the computer-based diagnostic process.In order to test hybrid-decision making, we created a prototype AF monitoring service. The service is based on Heart Rate (HR) sensors for signal acquisition as well as Internet of Things (IoT) technology for data communication and storage. These technologies enable transfer of HR data from patient to central cloud server. A deep learning system is used to analyze the data, which is then presented to a cardiologist when a dangerous condition is detected. This human specialist then works to verify the deep learning results based on the HR data and additional knowledge obtained through patient records or by personal interaction with the patient.A prerequisite for safety in any computer expert system is the clarity of purpose for the decision-making process. Health-care providers are considered customers who register patients with the AF monitoring service. The service delivers real-time diagnostic support by providing timely alarm messages and HR analysis. The safety critical decision then lies with the human practitioner.

Model to Assess Effectiveness of Regional Mass Media

The article presents the structure of the media in the Trans-Baikal Territory. The elements of the media system include leading information agencies, television channels, periodicals, determined by the media rating in the Trans-Baikal Territory. The mass media presented in the model have different technical and technological properties allowing them to represent the interests of various social and age groups. Taking into account the interests of the maximum number of the media product consumers makes it possible to assess the overall level of awareness of the population about the events and facts of regional social and economic development, which, in the authors' view, should be considered an indicator of the regional media effectiveness. The significance of this indicator is determined by the participation of the media in the formation of values, political views, moral and ethical guidelines and motives of the population. In this context, an evaluation of the overall performance of the system and partial performance indicators of its elements is an important management task. At the same time, the task is complicated because of the lack of a generally accepted system of indicators for assessing the processes of creating and transmitting information, as well as tools for their convolution. In accordance with the purpose of the study, the authors proposed a system of indicators for assessing the factors that determine the effectiveness of the processes of creating information products at each of the media in the region, as well as indicators of the overall effectiveness of the media system of the region. Given the differences in technologies for creation and transmission of information products, the authors solved the problem of comparability of indicators and data. At the stage of obtaining integral estimates, the problem of the convolution of the obtained indicators arose. To solve the problem of convolution, the apparatus of fuzzy logic and fuzzy logic inference was used. The obtained estimates revealed a high level of awareness of the population of the Trans-Baikal Region about the events, facts and processes of regional socio-economic development. The evaluation algorithm presented in the work allows one not only to assess the overall level of effectiveness of the regional media system, but also to compare the media systems of different regions, and to monitor the activities of individual media enterprises. The principal moment of practical application of the proposed algorithm is the possibility of building on its basis a computer expert system that allows to automate the calculations and the formation of an information base.