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Yang Zhou

Not to be confused with: Zhou Yang

Personal Details

First Name:Yang
Middle Name:
Last Name:Zhou
Suffix:
RePEc Short-ID:pzh802

Affiliation

(50%) School of Economics
Fudan University

Shanghai, China
http://www.econ.fudan.edu.cn/



No. 600. Guoquan Rd., Shanghai
RePEc:edi:sefudcn (more details at EDIRC)

(50%) Department of Operations Research and Financial Engineering (ORFE)
Princeton University

Princeton, New Jersey (United States)
http://orfe.princeton.edu/




RePEc:edi:doprius (more details at EDIRC)

Research output

as
Jump to: Articles

Articles

  1. Zhou, Yang & Zhang, Shuaishuai & Wu, Libo & Tian, Yingjie, 2019. "Predicting sectoral electricity consumption based on complex network analysis," Applied Energy, Elsevier, vol. 255(C).
  2. Zhou, Yang & Shi, Zhixiong & Shi, Zhengyu & Gao, Qing & Wu, Libo, 2019. "Disaggregating power consumption of commercial buildings based on the finite mixture model," Applied Energy, Elsevier, vol. 243(C), pages 35-46.
  3. Zhou, Yang & Ma, Rong & Su, Yun & Wu, Libo, 2019. "Too big to change: How heterogeneous firms respond to time-of-use electricity price," China Economic Review, Elsevier, vol. 58(C).

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Zhou, Yang & Zhang, Shuaishuai & Wu, Libo & Tian, Yingjie, 2019. "Predicting sectoral electricity consumption based on complex network analysis," Applied Energy, Elsevier, vol. 255(C).

    Cited by:

    1. Chen, Ying & Koch, Thorsten & Zakiyeva, Nazgul & Zhu, Bangzhu, 2020. "Modeling and forecasting the dynamics of the natural gas transmission network in Germany with the demand and supply balance constraint," Applied Energy, Elsevier, vol. 278(C).
    2. Zhang, Shuaishuai & Wu, Libo & Zhou, Yang, 2020. "The impact of negative list policy on sectoral structure: Based on complex network and DID analysis," Applied Energy, Elsevier, vol. 278(C).

  2. Zhou, Yang & Shi, Zhixiong & Shi, Zhengyu & Gao, Qing & Wu, Libo, 2019. "Disaggregating power consumption of commercial buildings based on the finite mixture model," Applied Energy, Elsevier, vol. 243(C), pages 35-46.

    Cited by:

    1. Khalilnejad, Arash & French, Roger H. & Abramson, Alexis R., 2020. "Data-driven evaluation of HVAC operation and savings in commercial buildings," Applied Energy, Elsevier, vol. 278(C).
    2. Jia, Mengshuo & Huang, Shaowei & Wang, Zhiwen & Shen, Chen, 2021. "Privacy-preserving distributed parameter estimation for probability distribution of wind power forecast error," Renewable Energy, Elsevier, vol. 163(C), pages 1318-1332.
    3. Himeur, Yassine & Alsalemi, Abdullah & Bensaali, Faycal & Amira, Abbes, 2020. "Robust event-based non-intrusive appliance recognition using multi-scale wavelet packet tree and ensemble bagging tree," Applied Energy, Elsevier, vol. 267(C).
    4. Pamulapati, Trinadh & Mallipeddi, Rammohan & Lee, Minho, 2020. "Multi-objective home appliance scheduling with implicit and interactive user satisfaction modelling," Applied Energy, Elsevier, vol. 267(C).
    5. Himeur, Yassine & Alsalemi, Abdullah & Bensaali, Faycal & Amira, Abbes, 2020. "Effective non-intrusive load monitoring of buildings based on a novel multi-descriptor fusion with dimensionality reduction," Applied Energy, Elsevier, vol. 279(C).

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