Zobrazeno 1 - 10
of 613
pro vyhledávání: '"Li, Hanying"'
Autor:
Zhou, Weiguo, Shen, Xiaomei, Xu, Zhimeng, Yang, Qingsong, Jiao, Mengyu, Li, Hanying, Zhang, Li, Ling, Juan, Liu, Hongbin, Dong, Junde, Suo, Anning
Publikováno v:
In Journal of Environmental Management November 2024 370
Autor:
Li, Hanying
In addition to being the natural genetic information carrier, DNA can also serve as a versatile material for construction of nanoscale objects. By using the base-pairing properties of DNA, we have been able to mass-produce nano-scale structures in a
Externí odkaz:
http://hdl.handle.net/10161/699
Autor:
He, Mei, Cai, Yanjun, Zhao, Xinnan, Xue, Gang, Lu, Yanbin, Cheng, Xing, Huang, Shouyi, Wang, Guozhen, Li, Ruoxin, Wang, Ting, Ma, Le, Wei, Yingying, Wu, Yuting, Lei, Shihao, Jia, Xuexue, Li, Hanying, Chang, Hong, Yan, Hong, Cheng, Hai
Publikováno v:
In Sedimentary Geology August 2024 470
Autor:
Li, Hanying, Guo, Pu, Liu, Guangping, Suo, Anning, Zhou, Weiguo, Yue, Weizhong, Jiao, Mengyu, Zhang, Li
Publikováno v:
In Journal of Environmental Management August 2024 365
Autor:
Jiao, Mengyu, Zhou, Weiguo, Long, Chao, Zhang, Li, Xu, Peng, Li, Hanying, Suo, Anning, Yue, Weizhong
Publikováno v:
In Journal of Cleaner Production 10 April 2024 449
Autor:
Deng, Xumeng, Chen, Kaihao, Pang, Kai, Liu, Xiaoting, Gao, Minsong, Ren, Jie, Yang, Guanwen, Wu, Guangpeng, Zhang, Chengjian, Ni, Xufeng, Zhang, Peng, Ji, Jian, Liu, Jianzhao, Mao, Zhengwei, Wu, Ziliang, Xu, Zhen, Zhang, Haoke, Li, Hanying
Publikováno v:
In Chinese Chemical Letters March 2024 35(3)
Autor:
Zhang, Li, Zhou, Weiguo, Jiao, Mengyu, Xie, Tian, Xie, Mujiao, Li, Hanying, Suo, Anning, Yue, Weizhong, Ding, Dewen, He, Weihong
Publikováno v:
In Science of the Total Environment 15 January 2024 908
Autor:
Duan, Pengzhen1 (AUTHOR) duanpengzhenz@163.com, Li, Hanying2 (AUTHOR) hanyingli@xjtu.edu.cn, Kathayat, Gayatri2 (AUTHOR) zhanghaiwei@xjtu.edu.cn, Zhang, Haiwei2 (AUTHOR) yfning@xjtu.edu.cn, Ning, Youfeng2 (AUTHOR), Zhu, Guangyou1 (AUTHOR) zhuguangyou@petrochina.com.cn, Cheng, Hai2 (AUTHOR) hanyingli@xjtu.edu.cn
Publikováno v:
Minerals (2075-163X). Apr2024, Vol. 14 Issue 4, p348. 16p.
Missing data are common in data analyses in biomedical fields, and imputation methods based on random forests (RF) have become widely accepted, as the RF algorithm can achieve high accuracy without the need for specification of data distributions or
Externí odkaz:
http://arxiv.org/abs/2004.14823
Machine learning iterative imputation methods have been well accepted by researchers for imputing missing data, but they can be time-consuming when handling large datasets. To overcome this drawback, parallel computing strategies have been proposed b
Externí odkaz:
http://arxiv.org/abs/2004.11195