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dc.contributor.authorPanda, A.-
dc.contributor.authorDyadyura, K.-
dc.contributor.authorSmorodin, A.-
dc.contributor.authorDmitrishin, D.-
dc.contributor.authorAntoshchuk, S.-
dc.date.accessioned2025-05-16T19:21:45Z-
dc.date.available2025-05-16T19:21:45Z-
dc.date.issued2024-
dc.identifier.citationPanda A. INTELLIGENT INFORMATION TECHNOLOGIES TO SUPPORT DECISIONMAKING WHEN APPLYING THE CAD/CAM/CAE SYSTEM OF DESIGN AND USING ADDITIVE TECHNOLOGIES / A. Panda, K. Dyadyura, A. Smorodin, D. Dmitrishin, S. Antoshchuk // MM Science Journal, 2024-June, 2024. - 7332-7339.en
dc.identifier.urihttp://dspace.opu.ua/jspui/handle/123456789/15196-
dc.description.abstractThe direction of research is the development of principles and methods for making scientifically based decisions in the design and additive manufacturing of bone substitutes based on apatite-biopolymer composites with functional properties depending on the nature of the localization of the cavity bone defect and its size. The relevance is due to the fact that the development of an intelligent decision-making support system based on neural network modeling, the development of methods for their training, tabagato-criterion optimization of design processes, will allow the creation of three-dimensional solid models of defects taking into account their spatial structure and bone substitutes for the synthesis of biomaterials with controlled composition, porosity and mechanical strength, which are optimal for a specific area of bone replacement, which will increase the effectiveness of treatment and prosthetics in orthopedics and traumatology. A set of methods for analyzing images of bone tissue, taking into account its spatial structure, which are obtained by sensors of different physical nature, with the use of neural network models, development of methods of their design, optimization, and training is proposed. A modification of the method of learning neural networks based on gradient descent, based on the application of the theory of nonlinear dynamics, is proposed. Corresponding theoretical provisions have been developed.en
dc.language.isoen_USen
dc.subjectMedical devicesen
dc.subject3D printingen
dc.subjectNonlinear dynamicen
dc.subjectTissue engineeringen
dc.subjectBone scaffoldsen
dc.subjectAdditive manufacturingen
dc.subjectConvolutional neural networksen
dc.subjectMedical imagingen
dc.subjectArtificial neural networksen
dc.titleINTELLIGENT INFORMATION TECHNOLOGIES TO SUPPORT DECISIONMAKING WHEN APPLYING THE CAD/CAM/CAE SYSTEM OF DESIGN AND USING ADDITIVE TECHNOLOGIESen
dc.typeArticleen
opu.citation.firstpage7332en
opu.citation.lastpage7339en
Располагается в коллекциях:2024



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