A Developed Decision-Making Algorithm in Intelligent Control Systems Based on the Asc-Analysis and the “Eidos” System

Lutsenko, Y. V.; Pechurina, E. K.; Sergeev, A. E.

doi:10.21515/1990-4665-160-009

Cited by 3 publications

(4 citation statements)

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“…The Eidos system model cannot be the same as the knowledge representation neural network model in that [29,30]: (i) The direct counting method, which is based on a well-theorized information theory model (similar to Bayesian networks), calculates the weight coefficients on the receptors instead of using the iterative backpropagation method;…”

Section: Resultsmentioning

confidence: 99%

Intelligent Risk Analysis of Investment Projects in the Extractive Industry

Al-Ansi,

Garad,

Ryabtsev

2024

JII

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This study introduces an advanced technology for risk analysis in investment projects within the extractive industry, specifically focusing on innovative mining ventures. The research primarily investigates various determinants influencing project risks, including production efficiency, cost, informational content, resource potential, organizational structure, external environmental influences, and environmental impacts. In addressing the research challenge, system-cognitive models from the Eidos intellectual framework are employed. These models quantitatively reflect the informational content observed across different gradations of descriptive scales, predicting the transition of the modelled object into a state corresponding to specific class gradations. A comprehensive analysis of strengths, weaknesses, opportunities and threats (SWOT) has been conducted, unveiling the dynamic interplay of development factors against the backdrop of threats and opportunities within mineral deposits exploitation projects. This analysis facilitates the identification of critical problem areas, bottlenecks, prospects, and risks, considering environmental considerations. The application of this novel intelligent technology significantly streamlines the development process for mining investment projects, guiding the selection of ventures that promise enhanced production efficiency, cost reduction, and minimized environmental harm. The methodological approach adopted in this study aligns with the highest standards of academic rigour, ensuring consistency in the use of professional terminology throughout the article and adhering to the stylistic and structural norms prevalent in leading academic journals. By leveraging an intelligent, systematic framework for risk analysis, this research contributes valuable insights into optimizing investment decisions in the mining sector, emphasizing sustainability and economic viability.

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Section: Resultsmentioning

confidence: 99%

Intelligent Risk Analysis of Investment Projects in the Extractive Industry

Al-Ansi,

Garad,

Ryabtsev

2024

JII

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“…Similar action, if all objects are not assigned to any of the classes, then the error of the 2nd kind will turn to zero, however, in this case, the non-identification error will be maximum. Thus, it is necessary to choose a certain threshold, such that the average number of errors of the 1st and 2nd kind is minimized, which is implemented in the Eidos system [19]. The Eidos system identifies the objects of the training sample, the classification vector of which is already known, and then calculates the weighted average identification error (integral validity), as well as the identification error with each class (differential validity).…”

Section: Formation and Verification Of Modelsmentioning

confidence: 99%

“…Modern intelligent systems perform automated processing of large databases containing signs of diseases, which ensures the diagnosis and classification of human diseases [8][9][10]. The purpose of this article is to use automated system-cognitive analysis (ASC-analysis) to identify the diseases of patients with the most common chronic diseases at an early stage [11]. To process medical data using ASC analysis, it is necessary to perform a machine learning procedure, i.e., develop representative databases for the types of diseases To achieve this goal, we need free access to large databases and a methodology that will help transform this data into a form which is necessary for working in an artificial intelligence system.…”

Section: Introductionmentioning

confidence: 99%

The Use of Large Databases for Diagnosing Human Diseases at Early Stage

Al-Ansi,

Ryabtsev,

Utkina

2023

IJAIDM

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The purpose of this article is to demonstrate the ability of the Eidos intellectual system to recognize human diseases at an early stage by processing large databases containing signs of diseases. To study the signs of diseases, it is proposed to use an automated system-cognitive analysis implemented in the Eidos intellectual system. Automated system-cognitive analysis extracts information from large databases and forms knowledge from them that makes it possible to recognize human diseases. In the process of forming models, the amount of information is calculated in the value of the factor by which the modeling object will pass under its influence to a certain state corresponding to the class. This allows for comparable and correct processing of heterogeneous information about observations of the object of modeling, presented in different types of measuring scales and different units of measurement. The results of recognition of the following diseases were obtained with high reliability: chronic kidney disease, lung cancer, breast cancer, liver disease, risks of developing diabetes and stroke. The results of the study can be applied in medical institutions in many countries, since the Eidos system is freely available on the Internet.

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“…SWOT-анализ был предложен в 1963 г. в Гарварде на конференции по проблемам бизнес-политики профессором К. Эндрюсом и является широко известным и общепризнанным методом стратегического планирования [10]. Данный анализ применяется для выявления факторов конкурентного окружения в качестве отдельного этапа оценки и структурирования информации, планирования и реализации, конкурентной разведки [11, с.…”

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Conceptual foundations of research of life strategies of rural youth in Belarus

Balich

2023

Vescì Akademìì navuk Belarusì. Seryâ gumanitarnyh navuk

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The article presents conceptual foundations of a theoretical and applied study of life strategies of the rural youth. An integral model for the analysis of life strategies has been proposed, aimed at identifying the main factors that shape, promote and hinder the implementation of various youth strategies in the context of life plans and orientations, requests, motivations, values of this social group, as well as taking into account the needs and prospects for the development of rural areas, agrarian industries. A method of empirical study of the life strategies of the rural youth has been proposed in the form of a scheme with the allocation of specific components of the analysis of socio-economic, socio-cultural and leisure, consumer strategies, as well as strategies for professional self-realization. Particular attention is paid to the demand for methods of managing regional development: strategic planning, project approach, which are used after studying of scientific literature and conducting surveys among the local population to model the socio-cultural development of rural areas on the basis of public opinion, statistical indicators of economic, social, cultural development. The importance of applying an interdisciplinary approach is noted, with taking into account the specifics of a particular region and the socio-demographic characteristics of young people, the need to develop indicators for assessing the effectiveness of the functioning of the economy, culture, education, healthcare both in the republic and in its rural areas, regions.

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A Developed Decision-Making Algorithm in Intelligent Control Systems Based on the Asc-Analysis and the “Eidos” System

Cited by 3 publications

References 0 publications

Intelligent Risk Analysis of Investment Projects in the Extractive Industry

Intelligent Risk Analysis of Investment Projects in the Extractive Industry

The Use of Large Databases for Diagnosing Human Diseases at Early Stage

Conceptual foundations of research of life strategies of rural youth in Belarus

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