Zhiping Chen

Xi'an Jiaotong University

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Jia Liu

Xi'an Jiaotong University

Ruiyue Lin

Wenzhou University

Peng Yang

Xi'an Jiaotong University

Jie Jiang

Chongqing University

Bingbing Ji

Xi'an Jiaotong University

Liyuan Wang

Sun Yat-sen University

Ling Feng

Zhongnan Hospital of Wuhan University

Qihong Duan

Beijing Jiaotong University

Youpan Han

Xi'an Polytechnic University

Qianhui Hu

Xi'an Jiaotong University

Cooperative Institutions

Xi'an Jiaotong University

Chinese Academy of Sciences

Zhejiang Center for Disease Control and Prevention

Zhejiang University

Shanghai Jiao Tong University

Hangzhou Dianzi University

University of Chinese Academy of Sciences

Sun Yat-sen University

Tsinghua University

Dongguan University of Technology

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Research on Petersen Graphs and Hyper-cubes Connected Interconnection Networks

Lecture notes in computer science (2006)

Lei Wang Zhiping Chen

Petersen graph

Routing algorithm

10.1007/11859802_49

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Citations (4)

Closed-Form Optimal Portfolios of Distributionally Robust Mean-CVaR Problems with Unknown Mean and Variance

Applied Mathematics & Optimization (2017)

Jia Liu Zhiping Chen Abdel Lisser Zhu-Jia Xu

CVAR

Robust Optimization

10.1007/s00245-017-9452-y

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Citations (22)

Design and implementation of three-phase two-bridge advanced neutral point clamped three-level photovoltaic inverter

2021 24th International Conference on Electrical Machines and Systems (ICEMS) (2014)

Liqiang Yuan Yang Cao Fanbo He Junchao Ma Zhiping Chen

The new topology of photovoltaic inverters is paid more and more attention in order to match the higher performance requirement in PV applications, recently. This paper presents a hybrid structure PV inverter, which combines the topology of the advanced neutral point clamped three-level and the one of three phases with two bridges. Based on the description of the new feature of this structure, the key parameters of this inverter, on both sides of the main circuit and the control strategy, are analyzed and designed according to its operation conditions. Then, the 10kW/600V prototype inverter is implemented and tested in an actual experimental platform. Under the different parameters of main circuit and control strategy, the experimental result to illustrate the inverter performance are obtained and compared.

Grid-tie inverter

10.1109/icems.2014.7013597

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Citations (3)

The quasi-arithmetic intuitionistic fuzzy OWA operators

Knowledge-Based Systems (2011)

Wei Yang Zhiping Chen

Operator (biology)

Belief structure

Choquet integral

10.1016/j.knosys.2011.10.009

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Citations (68)

Regime-dependent Robust Risk Measures with Application in Portfolio Selection

Procedia Computer Science (2014)

Jia Liu Zhiping Chen

Abstract Current robust risk measures or portfolio selection models are usually derived under the worst-case analysis, which makes the investment decision too conservative and could not reflect the change of uncertainty sets with respect to different market environ- ments. We use the regime switching technique to describe the time-varying uncertainty set of the first and second order moments, and propose two kinds of robust risk measures: worst regime risk measure and mixed worst-case risk measure. These new risk measures have good properties and the robust portfolio selection models derived from them can be efficiently solved in polynomial time. Empirical results show the reasonability and efficiency of our new models.

Spectral risk measure

Robust Optimization

Dynamic risk measure

Time consistency

10.1016/j.procs.2014.05.277

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Citations (10)

Moment Matching: A New Optimization-Based Sampling Scheme for Uncertainty Quantification of Reactor-Physics Analysis

Nuclear Science and Engineering (2021)

Bingbing Ji Zhiping Chen Jia Liu Liangzhi Cao Zhuojie Sui

Because of the complexity of the nuclear reactor system, traditional statistical sampling methods, such as random sampling and Latin hypercube sampling, often lead to unstable uncertainty quantification results of the reactor physics analysis. In order to make the analysis results robust, traditional sampling methods require a large number of samples, which brings a huge computation cost. For this reason, this paper proposes a new sampling scheme based on the moment matching method to generate efficient samples for the uncertainty quantification of reactor physics calculations. A linear programming model is established to minimize the deviations of the first- and second-order moments. The generated samples can better reflect the statistical characteristics of the real distribution than classical sampling methods. A series of numerical experiments is carried out to demonstrate the superiority of the proposed moment matching sampling method, which can quickly provide more reliable uncertainty quantification results with a small sample size.

Latin Hypercube Sampling

Uncertainty Quantification

10.1080/00295639.2021.1923338

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Citations (2)

Data-driven Stochastic Programming with Distributionally Robust Constraints Under Wasserstein Distance: Asymptotic Properties

Journal of the Operations Research Society of China (2020)

Mei Yu Zhiping Chen Bingbing Ji Zhu-Jia Xu Jia Liu

Robust Optimization

10.1007/s40305-020-00313-w

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Citations (4)