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27 March 2024 A computational optimization method for measuring and extracting correlation information between variables: taking the evaluation index system as an example
Geng Xinzhou, Wang Hao, Xu Zhibo, Zou Jing, Chen Zhiyi
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Proceedings Volume 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023); 131053X (2024) https://doi.org/10.1117/12.3026731
Event: 3rd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 2023, Qingdao, China
Abstract
The measurement and extraction of relevant information among variables belongs to the research scope of information theory. In the index evaluation system, there is a common correlation among index variables. The weighted summation method is generally used for the evaluation of indexes, and the relevant information among indexes will be repeatedly calculated, resulting in a large evaluation result. Therefore, this paper proposes a calculation optimization method for measuring and extracting relevant information between index variables. By studying the index correlation types, this paper defines the staple existence forms of relevant information, uses the more applicable global sensitivity algorithm to estimate the amount of relevant information, combing with the weight method to extract and reduce the amount of relevant information from relatively unimportant indexes, to realize the correction of index evaluation results. Based on the university journals cited statistics to verify the method mentioned in this paper, the results show that this method can effectively correct the index evaluation results.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Geng Xinzhou, Wang Hao, Xu Zhibo, Zou Jing, and Chen Zhiyi "A computational optimization method for measuring and extracting correlation information between variables: taking the evaluation index system as an example", Proc. SPIE 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 131053X (27 March 2024); https://doi.org/10.1117/12.3026731
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KEYWORDS
Mathematical optimization
Monte Carlo methods
Correlation coefficients
Information theory
Statistical methods
Statistical analysis
Information science
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