Study on Sustainable increase and system Analysis of Grain based on Principal component Analysis and Grey Prediction algorithm
DOI: 10.23977/agrfem.2021.040102 | Downloads: 15 | Views: 505
Zipeng Zhou 1, Zhijie Cao 1, Ziyi Liu 1, Haoran Li 1, Guibin Feng 1
1 School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, Guangdong, 510006
Corresponding AuthorZipeng Zhou
Food systems are essential to economic life because they provide the capacity that people need to live and work. For a long time, the food system has not received enough attention. But between 2019 and 2020, the COVID-19 pandemic left half of the planet closed. The food shortage caused by the COVID-19 pandemic shows the fragility of the highly centralized and immediate global food supply chain. In the process of economic reconstruction, the global food system should be improved. The paper provides a practical reference for solving the global food problem. In particular, this paper evaluates the advantages and disadvantages of the established model, comprehensively considering production, social, technical, environmental, economic and other factors, based on principal component analysis, grey prediction method and logistic model, our team establishes a comprehensive evaluation model of sustainable food system. In the process of analysis, we found that the principal component analysis method when the symbol of the factor load of the module is positive and negative, which reduces the clarity of our model, so we slightly improve our model. Rationalize the negative factor to zero and finally help us to get the final food system plan.
KEYWORDSSustainable development, principal component analysis, comprehensive index system
CITE THIS PAPER
Zipeng Zhou, Zhijie Cao, Ziyi Liu, Haoran Li, Guibin Feng, Study on Sustainable increase and system Analysis of Grain based on Principal component Analysis and Grey Prediction algorithm. Agricultural & Forestry Economics and Management (2021) Vol. 4: 6-10. DOI: http://dx.doi.org/10.23977/agrfem.2021.040102
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