Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Shanwen Guan"'
Publikováno v:
Electronics Letters, Vol 60, Iss 3, Pp n/a-n/a (2024)
Abstract Wireless signals are commonly subject to diverse and complex noise interference. The typical assumption of Gaussian white noise often oversimplifies the noise, resulting in reduced accuracy in estimating the direction of arrival (DOA), espec
Externí odkaz:
https://doaj.org/article/10eb558a87af4bbe9d213931ba95af74
Publikováno v:
Electronics Letters, Vol 58, Iss 25, Pp 1002-1005 (2022)
Abstract Direction‐of‐arrival (DOA) estimation based on sparse Bayesian learning (SBL) framework has attracted extensive attention. The accuracy of on‐grid DOA estimation is restricted by the prescribed grid, while off‐grid approaches resolve
Externí odkaz:
https://doaj.org/article/bd5c62a421cb4b58b5cda1284807bb19
Publikováno v:
2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b6d6dc6a0484d26202f55de7555432d8
https://doi.org/10.1109/cniot55862.2022.00022
https://doi.org/10.1109/cniot55862.2022.00022
Autor:
Shanwen Guan, Xiaonan Luo
Publikováno v:
2021 11th International Conference on Intelligent Control and Information Processing (ICICIP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2b01325213e05674b2bc489150bd0534
https://doi.org/10.1109/icicip53388.2021.9642157
https://doi.org/10.1109/icicip53388.2021.9642157
Publikováno v:
ICACI
With the rapid development of the location service industry, various positioning technologies have emerged. Recently, the mainstream indoor positioning technologies include WiFi positioning and Bluetooth positioning. Various positioning methods have
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0a2fcdd856acf09198a068321bd44128
https://doi.org/10.1109/icaci52617.2021.9435887
https://doi.org/10.1109/icaci52617.2021.9435887
Publikováno v:
ICACI
In this paper, a novel group-based swarm optimizer (GSO) is proposed for large scale optimization. Inspired from the group learning behavior in human society, the hierarchical learning are involved in GSO. In the mass learning stage, GSO randomly pic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::44bf2ded7fec8e1259496c2d93bca993
https://doi.org/10.1109/icaci49185.2020.9177743
https://doi.org/10.1109/icaci49185.2020.9177743
Publikováno v:
ICACI
China is a country with frequent landslide disasters, and the Three Gorges Reservoir area is a landslide disaster-prone area and a serious disaster area. GPS surface displacement monitoring is an important means of landslide stability monitoring. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eae6740035babc5e8f7c50c15415e32b
https://doi.org/10.1109/icaci.2019.8778620
https://doi.org/10.1109/icaci.2019.8778620
Publikováno v:
ICACI
This paper presents a new hybrid model for land-slide distance prediction. In the model, the cumulative displacement are divided into three parts: the trend term, the period term, and the random noise obtained by the wavelet domain de-nosing method a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d0d3a86caa241c0b77f4fcfeee9616c6
https://doi.org/10.1109/icaci.2019.8778500
https://doi.org/10.1109/icaci.2019.8778500
Publikováno v:
2018 7th International Conference on Digital Home (ICDH).
The surface of the landslide in the Three Gorges Reservoir area has a "step-like" feature. Landslide displacement prediction method based on displacement response component model is one of the main methods for the prediction of landslide displacement
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::34e3ff9b3aad398a143d4c774452e2ef
https://doi.org/10.1109/icdh.2018.00039
https://doi.org/10.1109/icdh.2018.00039
Publikováno v:
2018 7th International Conference on Digital Home (ICDH).
This study demonstrates a model for the prediction of active landslide displacement based on the extreme learning machine (ELM) with multiple factors. The particle swarm optimization (PSO) model is selected to optimize the parameters of ELM. Firstly,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78f63d95db79c05f12e1d561052b2718
https://doi.org/10.1109/icdh.2018.00048
https://doi.org/10.1109/icdh.2018.00048