Xiuli Shen

Prof. Xiuli Shen


Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 December 2017 in Structural and Multidisciplinary Optimization
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Journal Article
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CYCheng Yan
Cheng Yan
XSXiuli Shen
Xiuli Shen
FGFushui Guo
Fushui Guo

29 November 2022 in RSC Advances
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Journal Article
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HLHuan Liu
Huan Liu
HMHaibo Meng
Haibo Meng
HCHongbin Cong
Hongbin Cong
XSXiuli Shen
Xiuli Shen
XCXueli Chen
Xueli Chen
JDJinhang Dai
Jinhang Dai
Kinetic analysis of ethyl levulinate (EL) production from ball-milled corn stover catalyzed by Brønsted (B) acidic ionic liquid [Bmim-SO3H][HSO4] (SO3H-IL) and Lewis (L) acidic Al2(SO4)3 was performed in this study.

7 March 2019 in Structural and Multidisciplinary Optimization
Verified
Journal Article
Closed access
PDF file
CYCheng Yan
Cheng Yan
XSXiuli Shen
Xiuli Shen
FGFushui Guo
Fushui Guo
SZShiqi Zhao
Shiqi Zhao
LZLizhang Zhang
Lizhang Zhang

11 September 2020 in Archives of Computational Methods in Engineering
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Journal Article
Closed access
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XSXiuli Shen
Xiuli Shen
SZShuo Zhang
Shuo Zhang
XLXin Liu
Xin Liu
LGLongdong Gong
Longdong Gong
SDShaojing Dong
Shaojing Dong

23 April 2020 in The International Journal of Advanced Manufacturing Technology
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Journal Article
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XSXiuli Shen
Xiuli Shen
KGKun Gao
Kun Gao
SDShaojing Dong
Shaojing Dong

4 February 2020 in Energies
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Journal Article
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CYCheng Yan
Cheng Yan
JZJianfeng Zhu
Jianfeng Zhu
XSXiuli Shen
Xiuli Shen
JFJun Fan
Jun Fan
DMDong Mi
Dong Mi
ZQZhengming Qian
Zhengming Qian
Metamodels have become increasingly popular in the field of energy sources because of their significant advantages in reducing the computational cost of time-consuming tasks. Lacking the prior knowledge of actual physical systems, it may be difficult to find an appropriate metamodel in advance for a new task. A favorite way of overcoming this difficulty is to construct an ensemble metamodel by assembling two or more individual metamodels. Motivated by the existing works, a novel metamodeling approach for building the ensemble metamodels is proposed in this paper. By thoroughly exploring the characteristics of regression-type and interpolation-type metamodels, some useful information is extracted from the feedback of the regression-type metamodels to further improve the functional fitting capability of the ensemble metamodels. Four types of ensemble metamodels were constructed by choosing four individual metamodels. Common benchmark problems are chosen to compare the performance of the individual and ensemble metamodels. The results show that the proposed metamodeling approach reduces the risk of selecting the worst individual metamodel and improves the accuracy of the used individual metamodels.