IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i22p8491-d972073.html
   My bibliography  Save this article

A Multidimensional Adaptive Entropy Cloud-Model-Based Evaluation Method for Grid-Related Actions

Author

Listed:
  • Xiaoling Chen

    (School of Art and Media, China University of Geosciences, Wuhan 430074, China)

  • Weiwen Zhan

    (School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China)

  • Xingrui Li

    (School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China)

  • Jingkai Guo

    (School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China)

  • Jianyou Zeng

    (School of Art and Media, China University of Geosciences, Wuhan 430074, China)

Abstract

Smart grid training system needs to evaluate actions during power grid operations in order to complete training for relevant personnel. The commonly used action evaluation methods are difficult for evaluating fine actions during power grid operations, and the evaluation results are subjective. The use of an effective method to evaluate the actions of the power grid operation is important for improving the smart grid training system, enhancing the skills of the trainers, and ensuring the personal safety of operators. This paper proposes a cloud attention mechanism and an evaluation method of grid-related actions based on a multidimensional adaptive entropy cloud model to complete the evaluation of fine actions in the grid’s operation process. Firstly, the OpenCV technique is used to obtain the data related to hand actions during grid operation and to extract the action features to complete the construction of multiscale date sets; then, the adaptive entropy weight matrix at different scales is constructed based on multiscale data sets using the cloud attention mechanism, and the basic cloud model is generated from original hand-action feature data; finally, the multidimensional adaptive entropy cloud model is constructed by the adaptive entropy weight matrix and the basic cloud model, and the multidimensional adaptive entropy cloud model obtained is compared with the multidimensional adaptive entropy cloud model generated based on the standard action features in the same space to obtain the evaluation level of the hand action. The results show that the evaluation method of grid-related actions based on the multidimensional adaptive entropy cloud model can solve the mutual mapping problem between quantitative indicators and qualitative evaluation results in the evaluation of grid operation processes relatively well, and it effectively solves the subjectivity of the weight assignment of evaluation indicators, which can be used for the evaluation of fine actions in the grid’s operation processes.

Suggested Citation

  • Xiaoling Chen & Weiwen Zhan & Xingrui Li & Jingkai Guo & Jianyou Zeng, 2022. "A Multidimensional Adaptive Entropy Cloud-Model-Based Evaluation Method for Grid-Related Actions," Energies, MDPI, vol. 15(22), pages 1-18, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8491-:d:972073
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/22/8491/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/22/8491/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ke-Qin Wang & Hu-Chen Liu & Liping Liu & Jia Huang, 2017. "Green Supplier Evaluation and Selection Using Cloud Model Theory and the QUALIFLEX Method," Sustainability, MDPI, vol. 9(5), pages 1-17, April.
    2. Fangqiuzi He & Yong Liu & Weiwen Zhan & Qingjie Xu & Xiaoling Chen, 2022. "Manual Operation Evaluation Based on Vectorized Spatio-Temporal Graph Convolutional for Virtual Reality Training in Smart Grid," Energies, MDPI, vol. 15(6), pages 1-17, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yong Liu & Weiwen Zhan & Yuan Li & Xingrui Li & Jingkai Guo & Xiaoling Chen, 2023. "Grid-Related Fine Action Segmentation Based on an STCNN-MCM Joint Algorithm during Smart Grid Training," Energies, MDPI, vol. 16(3), pages 1-19, February.
    2. Amir Abbas Shojaie & Sepideh Babaie & Emel Sayah & Davood Mohammaditabar, 2018. "Analysis and Prioritization of Green Health Suppliers Using Fuzzy ELECTRE Method with a Case Study," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 19(1), pages 39-52, March.
    3. Fang, Hong & Wang, Xu & Song, Wenyan, 2020. "Technology selection for photovoltaic cell from sustainability perspective: An integrated approach," Renewable Energy, Elsevier, vol. 153(C), pages 1029-1041.
    4. Magdalena Ramirez-Peña & Patricia Perez-Martinez & Manuel Otero-Mateo & Moises Batista, 2024. "Technological Advancements in Global Supply Chains: A Comparative Analysis of Sustainability in Aerospace and Shipbuilding Industries," Sustainability, MDPI, vol. 16(18), pages 1-15, September.
    5. Saeid Alaei & Seyed Hossein Razavi Hajiagha & Hannan Amoozad Mahdiraji & Jose Arturo Garza-Reyes, 2023. "Unveiling the role of sustainable supply chain drivers toward knowledge-based economy via a novel permutation approach: implications from an emerging economy," Operations Management Research, Springer, vol. 16(3), pages 1231-1250, September.
    6. Tomas Cherkos Kassaneh & Ettore Bolisani & Juan-Gabriel Cegarra-Navarro, 2021. "Knowledge Management Practices for Sustainable Supply Chain Management: A Challenge for Business Education," Sustainability, MDPI, vol. 13(5), pages 1-15, March.
    7. Luu Huu Van & Vincent F. Yu & Luu Quoc Dat & Canh Chi Dung & Shuo-Yan Chou & Nguyen Viet Loc, 2018. "New Integrated Quality Function Deployment Approach Based on Interval Neutrosophic Set for Green Supplier Evaluation and Selection," Sustainability, MDPI, vol. 10(3), pages 1-13, March.
    8. Xiaoli Tian & Zeshui Xu & Xinxin Wang & Jing Gu & Fawaz E. Alsaadi, 2019. "Decision Models to Find a Promising Start-Up Firm with Qualiflex under Probabilistic Linguistic Circumstance," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1379-1402, July.
    9. Wang, Xu & Fang, Hong & Fang, Siran, 2020. "An integrated approach for exploitation block selection of shale gas—based on cloud model and grey relational analysis," Resources Policy, Elsevier, vol. 68(C).
    10. Ahmad Morshedi & Navid Nezafati & Sajjad Shokouhyar, 2024. "Motivational Factors Affecting Knowledge Sharing in Steel Industry Supply Chain: A Mixed Qualitative-Quantitative Method Analysis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 6273-6311, June.
    11. Mohammad Hossein Haghighi & Maryam Ashrafi, 2024. "A novel framework for risk management of software projects by integrating a new COPRAS method under cloud model and machine learning algorithms," Annals of Operations Research, Springer, vol. 338(1), pages 675-708, July.
    12. Wu, Zhongqun & Yang, Chan & Zheng, Ruijin, 2022. "Developing a holistic fuzzy hierarchy-cloud assessment model for the connection risk of renewable energy microgrid," Energy, Elsevier, vol. 245(C).
    13. Song, Wenyan & Xu, Zhitao & Liu, Hu-Chen, 2017. "Developing sustainable supplier selection criteria for solar air-conditioner manufacturer: An integrated approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1461-1471.
    14. Sema Akin Bas, 2024. "A Hybrid Approach Based on Consensus Decision Making for Green Supplier Selection in Automotive Industry," Sustainability, MDPI, vol. 16(7), pages 1-29, April.
    15. Hua Shi & Mei-Yun Quan & Hu-Chen Liu & Chun-Yan Duan, 2018. "A Novel Integrated Approach for Green Supplier Selection with Interval-Valued Intuitionistic Uncertain Linguistic Information: A Case Study in the Agri-Food Industry," Sustainability, MDPI, vol. 10(3), pages 1-18, March.
    16. José Roberto Mendoza-Fong & Jorge Luis García-Alcaraz & José Roberto Díaz-Reza & Juan Carlos Sáenz Diez Muro & Julio Blanco Fernández, 2017. "The Role of Green and Traditional Supplier Attributes on Business Performance," Sustainability, MDPI, vol. 9(9), pages 1-16, August.
    17. Jianghong Zhu & Yanlai Li, 2018. "Green Supplier Selection Based on Consensus Process and Integrating Prioritized Operator and Choquet Integral," Sustainability, MDPI, vol. 10(8), pages 1-22, August.
    18. Ziyuan Liu & Yingzhao Wu & Tianle Liu & Xiaoxue Wang & Wenzhuo Li & Ying Yin & Xiangfei Xiao, 2021. "Double Path Optimization of Transport of Industrial Hazardous Waste Based on Green Supply Chain Management," Sustainability, MDPI, vol. 13(9), pages 1-19, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8491-:d:972073. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.