IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i20p3796-d942719.html
   My bibliography  Save this article

Risk Evaluation Model of Coal Spontaneous Combustion Based on AEM-AHP-LSTM

Author

Listed:
  • Xu Zhou

    (College of Science, North China University of Science and Technology, Tangshan 063210, China
    School of Mining Engineering, North China University of Science and Technology, Tangshan 063210, China)

  • Shangsheng Ren

    (School of Economics, North China University of Science and Technology, Tangshan 063210, China
    College of Yisheng, North China University of Science and Technology, Tangshan 063210, China)

  • Shuo Zhang

    (School of Basic Medical Sciences, North China University of Science and Technology, Tangshan 063210, China)

  • Jiuling Zhang

    (School of Mining Engineering, North China University of Science and Technology, Tangshan 063210, China)

  • Yibo Wang

    (College of Yisheng, North China University of Science and Technology, Tangshan 063210, China)

Abstract

Immediately and accurately assessing the risk of coal spontaneous combustion and taking targeted action are crucial steps in coal spontaneous combustion prevention and control. A new model, AEM-AHP-LSTM, was proposed to solve the weight calculation problem of multiobjective evaluation in the process of coal spontaneous combustion. Firstly, the key indicators of coal spontaneous combustion were analyzed and used as risk factors to establish an evaluation system. Next, the objective and subjective weights were calculated using AEM and AHP, respectively. The objective and subjective weights were then combined, and TOPSIS was used to calculate the score of the evaluation sample. Finally, the obtained evaluation samples were trained with the BP, RBF, and LSTM model to resolve the problem of model overdependence on historical data and achieve the auto-adapt adjustment of weight with data change. Additionally, data from 15 typical Chinese coal mines were applied to the model. The results indicate that, compared with the BP and RBF neural networks, the LSTM model has higher prediction accuracy, stronger generalization ability, and stronger practicability. The modeling and application findings show that the AEM-AHP-LSTM model was better appropriate for the risk assessment of coal spontaneous combustion. This method can potentially be further applied as reliable approach for the assessment of mine disaster risk.

Suggested Citation

  • Xu Zhou & Shangsheng Ren & Shuo Zhang & Jiuling Zhang & Yibo Wang, 2022. "Risk Evaluation Model of Coal Spontaneous Combustion Based on AEM-AHP-LSTM," Mathematics, MDPI, vol. 10(20), pages 1-16, October.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:20:p:3796-:d:942719
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/20/3796/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/20/3796/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. W. Na & Z. C. Zhao, 2021. "The comprehensive evaluation method of low-carbon campus based on analytic hierarchy process and weights of entropy," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(6), pages 9308-9319, June.
    2. Sarraf, Fatemeh & Nejad, Shabnam Hashemi, 2020. "Improving performance evaluation based on balanced scorecard with grey relational analysis and data envelopment analysis approaches: Case study in water and wastewater companies," Evaluation and Program Planning, Elsevier, vol. 79(C).
    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. Liu, Bingchun & Song, Jiangji & Wang, Qingshan & Xu, Yan & Liu, Yifan, 2023. "Charging station forecasting and scenario analysis in China," Transport Policy, Elsevier, vol. 139(C), pages 87-98.
    2. Jiayin Xu & Xu Gui & Kun Li & Guifen Jiang & Tao Wang & Zhen Xu, 2023. "Microgrid Robust Planning Model and Its Modification Strategy Based on Improved Grey Relational Theory," Sustainability, MDPI, vol. 15(3), pages 1-23, February.
    3. Zhang, Chengyu & Ma, Liangdong & Han, Xing & Zhao, Tianyi, 2024. "Reconstituted data-driven air conditioning energy consumption prediction system employing occupant-orientated probability model as input and swarm intelligence optimization algorithms," Energy, Elsevier, vol. 288(C).
    4. Ning Pang & Xiaoya Deng & Aihua Long & Lili Zhang & Xinchen Gu, 2022. "Evaluation of the Resilience of the Socio-Hydrological System of the Tarim River Basin in China and Analysis of the Degree of Barriers," Sustainability, MDPI, vol. 14(13), pages 1-20, June.
    5. Zhao, Xue & Xie, Chengyuan & Huang, Lu & Wang, Yaru & Han, Tongyun, 2023. "How digitalization promotes the sustainable integration of culture and tourism for economic recovery," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 988-1000.
    6. Chaplygin, V. & Moroz, V., 2022. "Decision making on the technology transfer in regional innovation cluster under uncertainty and risk," Journal of the New Economic Association, New Economic Association, vol. 53(1), pages 121-142.
    7. Wendong Zhu & Dahai Li & Limin Han, 2022. "Spatial–Temporal Evolution and Sustainable Type Division of Fishery Science and Technology Innovation Efficiency in China," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    8. Yuanyuan Luo & Da Ren, 2021. "Influence of the enterprise’s intelligent performance evaluation model using neural network and genetic algorithm on the performance compensation of the merger and acquisition parties in the commitmen," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-16, March.
    9. Weixue Lu & Hecheng Wu & Liwen Wang, 2023. "The optimal environmental regulation policy combination for high-quality economic development based on spatial Durbin and threshold regression models," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 7161-7187, July.
    10. Kaya, Gizem & Aydın, Umut & Ülengin, Burç & Karadayı, Melis Almula & Ülengin, Füsun, 2023. "How do airlines survive? An integrated efficiency analysis on the survival of airlines," Journal of Air Transport Management, Elsevier, vol. 107(C).
    11. Peigui Liu & Shuoya Cheng & Manting Shang & Yang Gao & Song Wei, 2023. "Effect of Weight of Water Resources Carrying Capacity Evaluation Index on Its Evaluation Results in Xinjiang, China," Sustainability, MDPI, vol. 15(3), pages 1-14, February.
    12. Ma, Shuaiyin & Huang, Yuming & Liu, Yang & Kong, Xianguang & Yin, Lei & Chen, Gaige, 2023. "Edge-cloud cooperation-driven smart and sustainable production for energy-intensive manufacturing industries," Applied Energy, Elsevier, vol. 337(C).
    13. Afrasiabi, Ahmadreza & Chalmardi, Mazyar Kaboli & Balezentis, Tomas, 2022. "A novel hybrid evaluation framework for public organizations based on employees’ performance factors," Evaluation and Program Planning, Elsevier, vol. 91(C).

    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:jmathe:v:10:y:2022:i:20:p:3796-:d:942719. 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.