GES Model :Combining Pearson Correlation Coefficient Analysis with Multilayer Perceptron

Chunyu Sui; Xinrui Li; Yinghang Song; Sirui Huang; Yunpeng Zan

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arXiv · 2209.06381

GES Model :Combining Pearson Correlation Coefficient Analysis with Multilayer Perceptron

Chunyu Sui·Xinrui Li·Yinghang Song·Sirui Huang·Yunpeng Zan

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Abstract

With the development of technological progress, mining on asteroids is becoming a reality. This paper focuses on how to distribute asteroid mineral resources in a reasonable way to ensure global equity. To distribute asteroid resources fairly, 7 primary indicators and 20 secondary indicators are introduced to build a mathematical model to evaluate global equity and the weights are given by Analytic Hierarchy Process (AHP). Then Global Equity Score(GES) Model based on 12 primary indicators and 40 secondary indicators is built and TOPSIS method is applied to rank all countries. A t-distribution probability density function is applied to simulate the rate of asteroid mining. The Backward Algorithm is applied to quantitatively measure the impact of changing indicators on global equity. Then Pearson correlation coefficient analysis is conducted for each indicator, and t-test is performed lastly. The results demonstrate that asteroid mining promotes global equity that poor countries can be allocated slightly more mineral resources, and a schedule of the implementation of each measure is given. To gain more insight, sensitivity analysis is conducted and the results demonstrate that scores vary less than 7%. It can be concluded that our GES model have great potential as its robustness, accuracy and strengths.

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Chunyu Sui, Xinrui Li, Yinghang Song, Sirui Huang, Yunpeng Zan. 2022-09-14. GES Model :Combining Pearson Correlation Coefficient Analysis with Multilayer Perceptron. https://arxiv.org/abs/2209.06381

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