A comparative analysis of the principal component analysis and entropy weight methods to establish the indexing measurement

Wu, Robert M. X. and Zhang, Zhongwu and Yan, Wanjun and Fan, Jianfeng and Gou, Jinwen and Liu, Bao and Gide, Ergun and Soar, Jeffrey ORCID: https://orcid.org/0000-0002-4964-7556 and Shen, Bo and Fazal-e-Hasan, Syed and Liu, Zengquan and Zhang, Peng and Wang, Peilin and Cui, Xinxin and Peng, Zhanfei and Wang, Ya (2022) A comparative analysis of the principal component analysis and entropy weight methods to establish the indexing measurement. PLoS One, 17 (1):e0262261. pp. 1-26.

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Abstract

Background: As the world's largest coal producer, China was accounted for about 46% of global coal production. Among present coal mining risks, methane gas (called gas in this paper) explosion or ignition in an underground mine remains ever-present. Although many techniques have been used, gas accidents associated with the complex elements of underground gassy mines need more robust monitoring or warning systems to identify risks. This paper aimed to determine which single method between the PCA and Entropy methods better establishes a responsive weighted indexing measurement to improve coal mining safety. Methods: Qualitative and quantitative mixed research methodologies were adopted for this research, including analysis of two case studies, correlation analysis, and comparative analysis. The literature reviewed the most-used multi-criteria decision making (MCDM) methods, including subjective methods and objective methods. The advantages and disadvantages of each MCDM method were briefly discussed. One more round literature review was conducted to search publications between 2017 and 2019 in CNKI. Followed two case studies, correlation analysis and comparative analysis were then conducted. Research ethics was approved by the Shanxi Coking Coal Group Research Committee. Results: The literature searched a total of 25,831publications and found that the PCA method was the predominant method adopted, and the Entropy method was the second most widely adopted method. Two weighting methods were compared using two case studies. For the comparative analysis of Case Study 1, the PCA method appeared to be more responsive than the Entropy. For Case Study 2, the Entropy method is more responsive than the PCA. As a result, both methods were adopted for different cases in the case study mine and finally deployed for user acceptance testing on 5 November 2020. Conclusions: The findings and suggestions were provided as further scopes for further research. This research indicated that no single method could be adopted as the better option for establishing indexing measurement in all cases. The practical implication suggests that comparative analysis should always be conducted on each case and determine the appropriate weighting method to the relevant case. This research recommended that the PCA method was a dimension reduction technique that could be handy for identifying the critical variables or factors and effectively used in hazard, risk, and emergency assessment. The PCA method might also be well-applied for developing predicting and forecasting systems as it was sensitive to outliers. The Entropy method might be suitable for all the cases requiring the MCDM. There is also a need to conduct further research to probe the causal reasons why the PCA and Entropy methods were applied to each case and not the other way round. This research found that the Entropy method provides higher accuracy than the PCA method. This research also found that the Entropy method demonstrated to assess the weights of the higher dimension dataset was higher sensitivity than the lower dimensions. Finally, the comprehensive analysis indicates a need to explore a more responsive method for establishing a weighted indexing measurement for warning applications in hazard, risk, and emergency assessments.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Current - Faculty of Business, Education, Law and Arts - School of Business (18 Jan 2021 -)
Faculty/School / Institute/Centre: Current - Faculty of Business, Education, Law and Arts - School of Business (18 Jan 2021 -)
Date Deposited: 17 Mar 2022 01:16
Last Modified: 21 Sep 2022 00:34
Uncontrolled Keywords: methane gas, ignition, principal component analysis
Fields of Research (2008): 10 Technology > 1099 Other Technology > 109999 Technology not elsewhere classified
Fields of Research (2020): 49 MATHEMATICAL SCIENCES > 4999 Other mathematical sciences > 499999 Other mathematical sciences not elsewhere classified
Socio-Economic Objectives (2008): B Economic Development > 84 Mineral Resources (excl. Energy Resources) > 8499 Other Mineral Resources (excl. Energy Resources) > 849999 Mineral Resources (excl. Energy Resources) not elsewhere classified
Socio-Economic Objectives (2020): 25 MINERAL RESOURCES (EXCL. ENERGY RESOURCES) > 2599 Other mineral resources (excl. energy resources) > 259999 Other mineral resources (excl. energy resources) not elsewhere classified
Identification Number or DOI: https://doi.org/10.1371/journal.pone.0262261
URI: http://eprints.usq.edu.au/id/eprint/46945

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