Zobrazeno 1 - 10
of 351
pro vyhledávání: '"Guangmin Hu"'
Publikováno v:
Artificial Intelligence in Geosciences, Vol 4, Iss , Pp 22-27 (2023)
Seismic facies analysis plays important roles in geological research, especially in sedimentary environment identification. Traditional method is mainly based on seismic waveform or attributes of a single seismic gather to classify the seismic facies
Externí odkaz:
https://doaj.org/article/5b3d70497d9a43cb9feacbc699db254c
Publikováno v:
Electronic Research Archive, Vol 31, Iss 3, Pp 1524-1542 (2023)
Identification of network vulnerability is one of the important means of cyberspace operation, management and security. As a typical case of network vulnerability, network cascading failures are often found in infrastructure networks such as the powe
Externí odkaz:
https://doaj.org/article/aad33cb425ca439aa602503af50a4059
Publikováno v:
Artificial Intelligence in Geosciences, Vol 3, Iss , Pp 203-208 (2022)
We propose to use a Few-Shot Learning (FSL) method for the pre-stack seismic inversion problem in obtaining a high resolution reservoir model from recorded seismic data. Recently, artificial neural network (ANN) demonstrates great advantages for seis
Externí odkaz:
https://doaj.org/article/82aa370df1a74079a0b7307806240592
Autor:
Guangmin Hu, Yanfeng Han, Sida Liu, Biao Yu, Wenqi Tang, Dong Li, Hui Xing, Xiangfa Liu, Jiao Zhang, Baode Sun
Publikováno v:
Materials & Design, Vol 230, Iss , Pp 111997- (2023)
Strength and ductility of structural materials are mutually exclusive in general due to the strength-ductility trade-off. Using in-situ pyrolysis of polycarbosilane in NiCr powder green compacts, we fabricated NiCr-based composites with micro-sized c
Externí odkaz:
https://doaj.org/article/7c5f7c540e8a485c81c7924607927dcf
Publikováno v:
Applied Sciences, Vol 13, Iss 24, p 13045 (2023)
The establishment of a three-dimensional velocity field is an essential step in seismic exploration, playing a crucial role in understanding complex underground geological structures. Accurate 3D velocity fields are significant for seismic imaging, o
Externí odkaz:
https://doaj.org/article/723acba4a7f94e98b94f52ef6329028c
Autor:
Yuanzhong Chen, Jingjing Zong, Chengxin Liu, Zhonglin Cao, Pengfei Duan, Jianguo Li, Guangmin Hu
Publikováno v:
Frontiers in Earth Science, Vol 11 (2023)
Recent advances in distributed acoustic sensing (DAS) technology have allowed more intense measurements of subsurface and environment events, providing improved geohazard monitoring and subsurface characterization. This study discussed the subsurface
Externí odkaz:
https://doaj.org/article/461496de7b8f4bccb66bd0af9dac63d2
In big data times, massive datasets often carry different relationships among the same group of nodes, analyzing on these heterogeneous relationships may give us a window to peek the essential relationships among nodes. In this paper, first of all we
Externí odkaz:
http://arxiv.org/abs/1511.09134
Publikováno v:
IEEE Access, Vol 9, Pp 12217-12229 (2021)
Tensor sparse coding (TSC) is a method used to excavate 3D volume structures extended by sparse coding (SC), which is increasingly applied in data noise attenuation. Existing TSC approaches control the intensity of noise attenuation by using a predet
Externí odkaz:
https://doaj.org/article/61ff4ce08a174c60af9e501e111fe69a
Publikováno v:
Artificial Intelligence in Geosciences, Vol 1, Iss , Pp 31-35 (2020)
Fault interpretation plays a critical role in understanding the crustal development and exploring the subsurface reservoirs such as gas and oil. Recently, significant advances have been made towards fault semantic segmentation using deep learning. Ho
Externí odkaz:
https://doaj.org/article/8e865be363ed446caaaad57573e59060
Publikováno v:
Artificial Intelligence in Geosciences, Vol 1, Iss , Pp 24-30 (2020)
Supervised machine learning algorithms have been widely used in seismic exploration processing, but the lack of labeled examples complicates its application. Therefore, we propose a seismic labeled data expansion method based on deep variational Auto
Externí odkaz:
https://doaj.org/article/7cbbadfcc1c04a78ba37cc8f8316f711