Багатокритеріальне моделювання в умовах неоднорідної невизначеності даних у роботах Скалозуба В.В.
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Date
2024
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Український державний університет науки і технологій, ННІ ≪Інститут промислових та бізнес технологій≫, ІВК ≪Системні технології≫, Дніпро
Abstract
UKR: Виконано узагальнення підходів до вирішення завдань багатокритеріального моделювання в умовах неоднорідної невизначеності даних, у тому числі отриманих при моніторингу з нерівномірними та нечіткими інтервалами. Усі розглянуті підходи були створенні під керівництвом та за безпосередньої участі проф. Скалозуба В. В. У роботі виділено основні підходи до моделювання на основі багатошарових конструктивно-продукційних, сепарабельних та реляційно-сепарабельних моделей. Отримані результати можуть бути використані для подальшого розвитку запропонованих ідей та підходів.
ENG: The problems of solving multi-criteria modeling tasks in conditions of heterogeneous data uncertainty are characteristic and relevant for many areas, in particular, transport and logistics, medical, and economic. This paper summarizes the approaches to solving these areas tasks, including cases for data obtained during monitoring with uneven and unclear intervals. All the considered approaches were created under the guidance and with the direct participation of prof. Skalozub V. V. The author's team, with his participation, illustrated examples of the use of models in the tasks of organizing multi-symbol sequences in transport (formation-dismantling of trains, order processing) and in the analysis and forecasting of states/events based on data on diabetes diseases. In this paper, the main approaches to modeling in conditions of heterogeneous data uncertainty based on multi-layer constructive-synthesizing, separable and relational-separable models are highlighted. Multi-layer constructive-synthesizing became new branch of develop constructive-synthesizing modeling. Their practical value currently lies in the possibility of obtaining a new form of implementation of the specified technological processes of railway transport. In the future, they can be applied to tasks that require step-by-step data processing with a clear demarcation of the relevant operations. The obtained results can be used for further development of the proposed ideas and approaches. It is promising to develop the identified approaches, including by combining them, as well as supplementing constructive-production models with a formalized description of constructive elements, including input data, by ontological means. The paper contains information about the figure and scientific work of V. Skalozub.
ENG: The problems of solving multi-criteria modeling tasks in conditions of heterogeneous data uncertainty are characteristic and relevant for many areas, in particular, transport and logistics, medical, and economic. This paper summarizes the approaches to solving these areas tasks, including cases for data obtained during monitoring with uneven and unclear intervals. All the considered approaches were created under the guidance and with the direct participation of prof. Skalozub V. V. The author's team, with his participation, illustrated examples of the use of models in the tasks of organizing multi-symbol sequences in transport (formation-dismantling of trains, order processing) and in the analysis and forecasting of states/events based on data on diabetes diseases. In this paper, the main approaches to modeling in conditions of heterogeneous data uncertainty based on multi-layer constructive-synthesizing, separable and relational-separable models are highlighted. Multi-layer constructive-synthesizing became new branch of develop constructive-synthesizing modeling. Their practical value currently lies in the possibility of obtaining a new form of implementation of the specified technological processes of railway transport. In the future, they can be applied to tasks that require step-by-step data processing with a clear demarcation of the relevant operations. The obtained results can be used for further development of the proposed ideas and approaches. It is promising to develop the identified approaches, including by combining them, as well as supplementing constructive-production models with a formalized description of constructive elements, including input data, by ontological means. The paper contains information about the figure and scientific work of V. Skalozub.
Description
О. Куроп’ятник: ORCID: 0000-0003-2286-884X
Keywords
умови невизначеності, нерівномірний та нечіткий інтервал вибірки, упорядкування мультипослідовностей елементів, сеперабельна модель, конструктивно-продукційне моделювання, конструктивна модель, інформаційні технології, conditions of uncertainty, uneven and fuzzy sampling interval, arrangement of multisequences of elements, separable model, constructive-synthesizing modeling, constructive model, information technologies, КІТ
Citation
Куроп’ятник О. С. Багатокритеріальне моделювання в умовах неоднорідної невизначеності даних у роботах Скалозуба В.В. Системні технології. Дніпро, 2024. Т. 6, № 155. С. 3–9. DOI: https://doi.org/10.34185/1562-9945-6-155-2024-01.