Zobrazeno 1 - 10
of 1 823
pro vyhledávání: '"WANG Xueli"'
Publikováno v:
Guangxi Zhiwu, Vol 44, Iss 5, Pp 840-851 (2024)
To investigate the effects of two different water sources, domestic sewage and nutrient solution, on residue decomposition and the transformation of chromium chemical forms in Cr (Ⅵ) contaminated constructed wetlands, a micro Coix lacryma-jobi cons
Externí odkaz:
https://doaj.org/article/ad3bab115f464d009c7254a37431022d
Publikováno v:
Journal of Causal Inference, Vol 12, Iss 1, Pp 1990-701 (2024)
In this article, we discuss both prospective and retrospective causal inferences, building on Neyman’s potential outcome framework. For prospective causal inference, we review criteria for confounders and surrogates to avoid the Yule–Simpson para
Externí odkaz:
https://doaj.org/article/9afaa895d80e49ba9e1fd5da930e34f1
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
This paper analyzes the influences on creative thinking by utilizing multivariate data integration methods and modular network-based integration methods. A creative drive gene identification algorithm was built using the network learning approach. Us
Externí odkaz:
https://doaj.org/article/4770421faa4149739be6b2b8ad943e7a
In observational studies, covariates with substantial missing data are often omitted, despite their strong predictive capabilities. These excluded covariates are generally believed not to simultaneously affect both treatment and outcome, indicating t
Externí odkaz:
http://arxiv.org/abs/2402.14438
Publikováno v:
MATEC Web of Conferences, Vol 336, p 05018 (2021)
With the development of new generation Internet technology, Digital Object Architecture (DOA)/Handle system plays an important role in industrial system. The development and technical characteristics of DOA/Handle technology is studied in this paper.
Externí odkaz:
https://doaj.org/article/1cdea753f1394f608dc496351f0188ac
Autor:
Chen, Junhao, wang, Xueli
In this article, we strengthen the proof methods of some previously weakly consistent variants of random forests into strongly consistent proof methods, and improve the data utilization of these variants, in order to obtain better theoretical propert
Externí odkaz:
http://arxiv.org/abs/2304.04240
Autor:
Wang, Xueli1,2 (AUTHOR) wangxueli@caas.cn, Liu, Qian1 (AUTHOR) liuqian00007@163.com, Wang, Juan3 (AUTHOR) gloria0826@163.com, Wang, Li1 (AUTHOR) wangli06@caas.cn, Tu, Hongtao1,2 (AUTHOR) tuhongtao@caas.cn, Zhang, Jinyong1 (AUTHOR) tuhongtao@caas.cn
Publikováno v:
Agronomy. Oct2024, Vol. 14 Issue 10, p2307. 11p.