Zobrazeno 1 - 10
of 514
pro vyhledávání: '"Properties prediction"'
Publikováno v:
Energy Science & Engineering, Vol 12, Iss 9, Pp 3730-3742 (2024)
Abstract In this study, the Structural Units‐Bonding Matrix will be introduced into the crude oil characteristics analysis, specifically engineered to depict the molecular intricacies of petroleum substances. This methodology synergizes the bonding
Externí odkaz:
https://doaj.org/article/15b1caf404fb428ba5d2a03dde31cc1d
Autor:
Xiaofan Zheng, Yoichi Tomiura
Publikováno v:
Journal of Cheminformatics, Vol 16, Iss 1, Pp 1-9 (2024)
Abstract Among the various molecular properties and their combinations, it is a costly process to obtain the desired molecular properties through theory or experiment. Using machine learning to analyze molecular structure features and to predict mole
Externí odkaz:
https://doaj.org/article/430ba32fd7324bccafcdd7cb1c754733
Publikováno v:
In Journal of Building Engineering 1 December 2024 98
Autor:
Elkatatny, Sally a, ⁎, Abd-Elaziem, Walaa b, c, d, Sebaey, Tamer A. d, Darwish, Moustafa A. e, Hamada, Atef f, ⁎⁎
Publikováno v:
In Journal of Materials Research and Technology November-December 2024 33:3976-3997
Autor:
Du, Yuanyuan a, Kang, Fengjin b, Huang, Zhangke a, Wang, Luyi a, Zhang, Ya a, Li, Decheng c, Zheng, Guanghui a, Zeng, Rong a, ⁎
Publikováno v:
In Computers and Electronics in Agriculture March 2025 230
Autor:
V.A. Milyutin, R. Bureš, M. Fáberová, Z. Birčáková, Z. Molčanová, B. Kunca, L.A. Stashkova, P. Kollár, J. Füzer
Publikováno v:
Journal of Materials Research and Technology, Vol 29, Iss , Pp 5060-5073 (2024)
The transition from the traditional “post-analysis” strategy for developing soft magnetic materials to an innovative “pre-design” one is highly desirable for the development of advanced electrical devices. In this work, we present the creatio
Externí odkaz:
https://doaj.org/article/2721652a6b134466b3c1b18d7f85aaf8
Publikováno v:
IEEE Access, Vol 12, Pp 19035-19058 (2024)
A comprehensive assessment of machine learning applications is conducted to identify the developing trends for Artificial Intelligence (AI) applications in the oil and gas sector, specifically focusing on geological and geophysical exploration and re
Externí odkaz:
https://doaj.org/article/9754568896f64fb6a5fff31aa826b3fc
Publikováno v:
Micromachines, Vol 15, Iss 9, p 1167 (2024)
This study developed a new metallography–property relationship neural network (MPR-Net) to predict the relationship between the microstructure and mechanical properties of 316L stainless steel built by laser powder bed fusion (LPBF). The accuracy R
Externí odkaz:
https://doaj.org/article/0c6a04f658a349d7887013a13041ab82
Publikováno v:
Machines, Vol 12, Iss 8, p 523 (2024)
Predicting the mechanical properties of Additive Manufacturing (AM) parts is a complex task due to the intricate nature of the manufacturing processes. This study presents a novel application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) to pr
Externí odkaz:
https://doaj.org/article/c77db6a0653e434293e804fe5602ae85
Publikováno v:
工程科学学报, Vol 45, Iss 7, Pp 1194-1204 (2023)
Data-driven material informatics is considered the fourth paradigm of materials research and development (R&D), which can greatly reduce R&D costs and shorten the R&D cycle. However, the data-driven method increases the risk of privacy disclosure whe
Externí odkaz:
https://doaj.org/article/ac72f2913c2b4efbac561884377cd372