Abstract
Based on a review and analysis of evaluation screening methods to determine the relevance, importance, and effectiveness of indicators, evaluation screening algorithms based on a comprehensive multifactor methods were constructed using gray relational clustering, vague analysis, and gray correlation analysis. The algorithm takes multiple factors into account, not only retaining the index system of the more important indicators but also allowing each index to be independent, so that both can be used in the overall index system without redundancy. On this basis, further analysis by validation ensures that the screening results are scientific and effective, providing new methods and ideas for the screening evaluation of complex systems. In addition, gray correlation analysis can be applied to evaluate the effectiveness of the overall approach, the degree of the curve in similar geometry to reflect the size of the effectiveness indicators, and the effectiveness of the inspection conducted. Exploratory research can broaden the scope of application of gray correlation analysis.
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Wang, C., Zhang, J., Wang, C., Yang, X., Li, F. (2015). Analysis and Construction of Evaluation Index Screening Methods Based on Comprehensive Multifactor Methods. In: Long, S., Dhillon, B.S. (eds) Proceedings of the 15th International Conference on Man–Machine–Environment System Engineering. MMESE 2015. Lecture Notes in Electrical Engineering, vol 356. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48224-7_53
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DOI: https://doi.org/10.1007/978-3-662-48224-7_53
Publisher Name: Springer, Berlin, Heidelberg
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