Zobrazeno 1 - 10
of 144
pro vyhledávání: '"Minqiang Xu"'
Autor:
Di Wang, Jing Zhang, Minqiang Xu, Lin Liu, Dongsheng Wang, Erzhong Gao, Chengxi Han, Haonan Guo, Bo Du, Dacheng Tao, Liangpei Zhang
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11632-11654 (2024)
Foundation models have reshaped the landscape of remote sensing (RS) by enhancing various image interpretation tasks. Pretraining is an active research topic, encompassing supervised and self-supervised learning methods to initialize model weights ef
Externí odkaz:
https://doaj.org/article/f1ebc4a04ca145599622a4482d62ea54
Publikováno v:
Alexandria Engineering Journal, Vol 64, Iss , Pp 97-105 (2023)
In this paper, we investigate an efficient technique for solving fractional integro-differential equations (FIDEs) that have numerous applications in various fields of science. The proposed technique is based upon the Legendre orthonormal polynomial
Externí odkaz:
https://doaj.org/article/74d5efb168814f23b5b35a8e94b89e4c
Publikováno v:
Journal of Marine Science and Engineering, Vol 11, Iss 12, p 2311 (2023)
Maritime transportation plays a critical role in global trade, and studies on maritime transportation safety management are of great significance to the sustainable development of the maritime industry. Consequently, there has been an increasing tren
Externí odkaz:
https://doaj.org/article/021e26f0e2cc4eeeaff87a424b03e38a
Publikováno v:
IEEE Access, Vol 8, Pp 91103-91115 (2020)
In recent years, Convolutional neural networks (CNNs) have achieved start-of-art performance in the fault diagnosis field. If there is no available information on the unseen operating conditions, the model trained on the seen operating condition cann
Externí odkaz:
https://doaj.org/article/53fba01ff9cc4cb6a901bbb973c856f3
Publikováno v:
IEEE Access, Vol 7, Pp 16616-16625 (2019)
A novel hybrid fault diagnosis method based on ensemble empirical mode decomposition and weighted adaptive multi-scale morphological analysis (WAMMA) is proposed to detect the early damage of gearboxes. In this method, we propose a characteristic fre
Externí odkaz:
https://doaj.org/article/5f4317953c8d4bce9be80456141ddddc
Publikováno v:
IEEE Access, Vol 7, Pp 186217-186227 (2019)
The prediction of the battery temperature and terminal voltage under dynamic load condition is crucial for a satellite battery management system. Restricted by parameter measurability and computing resources, equivalent circuit model has been commonl
Externí odkaz:
https://doaj.org/article/55523bb3710e45e9b00e684c70c67a0b
Publikováno v:
IEEE Access, Vol 7, Pp 38983-38995 (2019)
A new intelligent fault diagnosis algorithm of rotating machinery based on intrinsic characteristic-scale decomposition (ICD), generalized composite multi-scale fuzzy entropy (GCMFE), Laplacian score (LS), and particle swarm optimization-based suppor
Externí odkaz:
https://doaj.org/article/6daf8963cb544ca4b498a7ba7ace02d5
Publikováno v:
IEEE Access, Vol 7, Pp 109751-109762 (2019)
Aiming at the problem that the traditional similarity measurement methods cannot effectively measure the similarity of the time series with the difference both in the trend and detail, this paper proposes a new time series similarity measurement meth
Externí odkaz:
https://doaj.org/article/06dfafb9e64a4f04bac6a52861d50ed3
Publikováno v:
IEEE Access, Vol 7, Pp 129260-129290 (2019)
Data-driven fault diagnosis has been a hot topic in recent years with the development of machine learning techniques. However, the prerequisite that the training data and the test data should follow an identical distribution prevents the conventional
Externí odkaz:
https://doaj.org/article/d06ca9fd1c7a47b0ac3f6d4f5793cb40
Publikováno v:
Applied Sciences, Vol 11, Iss 22, p 10968 (2021)
With the complexity of the task requirement, multiple operating conditions have gradually become the common scenario for equipment. However, the degradation trend of monitoring data cannot be accurately extracted in life prediction under multiple ope
Externí odkaz:
https://doaj.org/article/2e3ab10801a149cbaa89efdf91bb768c