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INTELLIGENT INFORMATION TECHNOLOGIES TO SUPPORT DECISIONMAKING WHEN APPLYING THE CAD/CAM/CAE SYSTEM OF DESIGN AND USING ADDITIVE TECHNOLOGIES

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dc.contributor.author Panda, A.
dc.contributor.author Dyadyura, K.
dc.contributor.author Smorodin, A.
dc.contributor.author Dmitrishin, D.
dc.contributor.author Antoshchuk, S.
dc.date.accessioned 2025-05-16T19:21:45Z
dc.date.available 2025-05-16T19:21:45Z
dc.date.issued 2024
dc.identifier.citation Panda 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.uri http://dspace.opu.ua/jspui/handle/123456789/15196
dc.description.abstract The 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.iso en_US en
dc.subject Medical devices en
dc.subject 3D printing en
dc.subject Nonlinear dynamic en
dc.subject Tissue engineering en
dc.subject Bone scaffolds en
dc.subject Additive manufacturing en
dc.subject Convolutional neural networks en
dc.subject Medical imaging en
dc.subject Artificial neural networks en
dc.title INTELLIGENT INFORMATION TECHNOLOGIES TO SUPPORT DECISIONMAKING WHEN APPLYING THE CAD/CAM/CAE SYSTEM OF DESIGN AND USING ADDITIVE TECHNOLOGIES en
dc.type Article en
opu.citation.firstpage 7332 en
opu.citation.lastpage 7339 en


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