Zobrazeno 1 - 10
of 292
pro vyhledávání: '"Shi Zhenhua"'
Autor:
Xu Yan, Gao Daqiang, Shi Zhenhua, Zhang Jing, Yang Guijin, Zhang Jinlin, Wang Xinhua, Xue Desheng
Publikováno v:
Nanoscale Research Letters, Vol 5, Iss 8, Pp 1289-1294 (2010)
Abstract Preferred oriented ZnFe2O4 nanowire arrays with an average diameter of 16 nm were fabricated by post-annealing of ZnFe2 nanowires within anodic aluminum oxide templates in atmosphere. Selected area electron diffraction and X-ray diffraction
Externí odkaz:
https://doaj.org/article/154512a42b5348c2afbbdc5bb536339e
Autor:
Dong, Jingliang, Wu, Hao, Xie, Sui, Shang, Xiaopeng, Shi, Zhenhua, Tu, Zhen, Zhou, Peng, Zhang, Tingting
Publikováno v:
In Journal of Building Engineering 1 November 2024 96
Publikováno v:
In iScience 20 September 2024 27(9)
Autor:
Xie, Mengshan, Xu, Sheng, Su, Cheng-yue, Feng, Zu-yong, Chen, Yuandian, Shi, Zhenhua, Lian, Jiebo
With the characteristics of vertical take-off and landing and long endurance, tiltrotor has attracted considerable attention in recent decades for its potential applications in civil and scientific research. However, the problems of strong couplings,
Externí odkaz:
http://arxiv.org/abs/2111.02046
Publikováno v:
In Engineering Applications of Artificial Intelligence July 2024 133 Part D
Autor:
Xu, Min, Zhang, Jiayan, Shi, Zhenhua, He, Ziyang, Zhao, Yijing, Ling, Xiaoyang, Wang, Wenhua, Gong, Mingjie
Publikováno v:
In Journal of Ethnopharmacology 23 May 2024 326
Autor:
Dong, Jingliang, Chen, Leiwei, Li, Lianghua, Zhou, Peng, Shi, Zhenhua, Cai, Jinping, Zhang, Tingting
Publikováno v:
In Construction and Building Materials 16 February 2024 416
Publikováno v:
In Engineering Structures 1 January 2024 298
Publikováno v:
Information Sciences, 574:490:504, 2021
To effectively optimize Takagi-Sugeno-Kang (TSK) fuzzy systems for regression problems, a mini-batch gradient descent with regularization, DropRule, and AdaBound (MBGD-RDA) algorithm was recently proposed. This paper further proposes FCM-RDpA, which
Externí odkaz:
http://arxiv.org/abs/2012.00060
Autor:
Zhao, Changming, Wu, Dongrui, Huang, Jian, Yuan, Ye, Zhang, Hai-Tao, Peng, Ruimin, Shi, Zhenhua
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
Bootstrap aggregating (Bagging) and boosting are two popular ensemble learning approaches, which combine multiple base learners to generate a composite model for more accurate and more reliable performance. They have been widely used in biology, engi
Externí odkaz:
http://arxiv.org/abs/2003.09737