Zobrazeno 1 - 10 of 36 pro vyhledávání: '"Hongli Miao"'
1
Akademický článek
The Vertex Gutman Index and Gutman Index of the Union of Two Cycles
Autor: Yinzhen Mei, Hongli Miao
Publikováno v: Axioms, Vol 13, Iss 4, p 269 (2024)
The Wiener index is one of the most classic and widely used indicators in topology. It reflects the average distance of any node pair in the graph. It not only makes the boundaries of given graphs clearer but also continuously generates topological i
Externí odkaz: https://doaj.org/article/377929af8e8b4ebca5006aa04c9c740b
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2
Akademický článek
Timeliness of Correcting Baseline Error in Wide-Swath Altimeter Based on Reference Topography Data
Autor: Xiangying Miao, Lei Liu, Hongli Miao, Zhonghao Yang, Jing Wang, Qingjun Zhang
Publikováno v: Remote Sensing, Vol 15, Iss 10, p 2482 (2023)
The baseline error is a primary error source of the wide-swath altimeter, directly related to the cross-track distance, and can lead to serious height errors at the swath’s outer edge. Cross-calibration using discrepancies with reference data can e
Externí odkaz: https://doaj.org/article/312ae874287d4c47afccc6c21b87dd14
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3
Akademický článek
A novel model of estimating sea state bias based on multi-layer neural network and multi-source altimeter data
Autor: Hongli Miao, Yingting Guo, Guoqiang Zhong, Benxiu Liu, Guizhong Wang
Publikováno v: European Journal of Remote Sensing, Vol 51, Iss 1, Pp 616-626 (2018)
In this article, we propose a novel model for estimating sea state bias (SSB) based on multi-layer neural network and multi-source altimeter data from the Topex/Poseidon (T/P), Jason-2, and Jason-3 altimeters. Significant wave height (SWH), wind spee
Externí odkaz: https://doaj.org/article/0d85e0bc6b794577ac00e90a8684c01a
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4
Akademický článek
Using a stacked-autoencoder neural network model to estimate sea state bias for a radar altimeter.
Autor: Xiangying Miao, Hongli Miao, Yongjun Jia, Yingting Guo
Publikováno v: PLoS ONE, Vol 13, Iss 12, p e0208989 (2018)
This paper constructed a stacked-autoencoder neural network model (SAE model) to estimate sea state bias (SSB) based on radar altimeter data. Six cycles of the geophysical data record (GDR) from Jason-1/2 radar altimeters were used as a training data
Externí odkaz: https://doaj.org/article/12b3ae414c324e9b8ce3f1237c30f79b
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Plný text Recenzováno Digitální knihovna AV ČR
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