Zobrazeno 1 - 10
of 2 265
pro vyhledávání: '"Data reconstruction"'
Autor:
Fei Tan, Yanbin Jiang, Qian Lei, Hongtao Zhang, Lijun Zhang, Zhu Xiao, Guofu Xu, Yuyuan Zhao, Zhou Li
Publikováno v:
Journal of Materials Research and Technology, Vol 31, Iss , Pp 1326-1336 (2024)
Complex mapping relationships between high-entropy alloy compositions and performances struggle to precisely elucidate by traditional machine learning models, hindering the accurate and efficient design of high-performance alloys. In this work, a nov
Externí odkaz:
https://doaj.org/article/a6a9b478557945d5b7dac0aea97f9906
Publikováno v:
Journal of Agrometeorology, Vol 26, Iss 3 (2024)
Comprehensive climate time series data is indispensable for monitoring the impacts of climate change. However, observational datasets often suffer from data gaps within their time series, necessitating imputation to ensure dataset integrity for furth
Externí odkaz:
https://doaj.org/article/74c02ae0b80c4c098f2ac18b2131b64a
Autor:
Yundong GUO
Publikováno v:
CT Lilun yu yingyong yanjiu, Vol 33, Iss 2, Pp 149-158 (2024)
Due to limited acquisition conditions in the field, the seismic data is usually incomplete, which affects the following seismic data processing and seismic interpretation. To solve this problem, the seismic data needs reconstruction. The projection o
Externí odkaz:
https://doaj.org/article/96b91f26be49426397447d914283cf9b
Publikováno v:
IEEE Access, Vol 12, Pp 98816-98834 (2024)
In today’s era of increasing data complexity and pervasive noise, robust techniques for data processing, reconstruction, and denoising are crucial. Autoencoders, known for their adaptability in unsupervised learning, offer a strategic solution to t
Externí odkaz:
https://doaj.org/article/be0f5d7c7ee747a185e3ccdde244313e
Publikováno v:
IEEE Access, Vol 12, Pp 93033-93050 (2024)
Wireless Sensor Network (WSN) based Internet of Things (IoT) solutions are extensively deployed to monitor environmental parameters and physical conditions in various domains. However, wireless sensor nodes have limited energy sources and in many cas
Externí odkaz:
https://doaj.org/article/a95d3ddfcd5f4923810a5e0c9ec719f5
Publikováno v:
Journal of Hydrology: Regional Studies, Vol 52, Iss , Pp 101701- (2024)
Study area: The Manas River Basin (84°01′−86°32′E, 42°27′−45°21′N) on the northern slopes of the Tianshan Mountains and the Kaidu River Basin (82°18′−85°57′E, 40°54′−44°30′N) on the southern slopes. Study focus: Tradit
Externí odkaz:
https://doaj.org/article/221d9444623348c29b55a2592d27ea40
Publikováno v:
Remote Sensing, Vol 16, Iss 15, p 2713 (2024)
The Normalized Difference Vegetation Index (NDVI) is a crucial remote-sensing metric for assessing land surface vegetation greenness, essential for various studies encompassing phenology, ecology, hydrology, etc. However, effective applications of ND
Externí odkaz:
https://doaj.org/article/2dc8d18e58944dc6bf75d192686cb698
Publikováno v:
Sensors, Vol 24, Iss 14, p 4470 (2024)
An interpolation method, which estimates unknown values with constrained information, is based on mathematical calculations. In this study, we addressed interpolation from an image-based perspective and expanded the use of image inpainting to estimat
Externí odkaz:
https://doaj.org/article/5d6b80d2795b4dd0beb383da35c87cf8
Publikováno v:
Journal of Marine Science and Engineering, Vol 12, Iss 7, p 1220 (2024)
A well-performing data-driven sparse sensor deployment strategy is critical for marine monitoring systems, as it enables the optimal reconstruction of marine physical quantities with fewer sensors. However, ocean data typically contain substantial am
Externí odkaz:
https://doaj.org/article/3a022c2501bd4a788b4b926864077e7e