Research on Food Security Evaluation Model based on data implicit Distribution Mining algorithm
DOI: 10.23977/agrfem.2021.040106 | Downloads: 2 | Views: 125
Weiyao Li 1, Ziqi Bao 2, Jinyan Zhang 1
1 School of Communication Engineering, Beijing Jiaotong University, Beijing 100044
2 School of Economics and Management, Beijing Jiaotong University, Beijing 100044
Corresponding AuthorWeiyao Li
In recent years, the global food crisis has become increasingly serious. Therefore, we hope to build a new model of grain supply system to maximize the overall benefit of grain under the constraints of objective conditions. We first collect agricultural data from countries with different levels of development. Then, we use entropy method and TOPSIS model to construct the evaluation model of grain supply system, and compare the internal analysis and weight of different data. After comprehensively measuring the four aspects of grain production conditions, environmental sustainability, fairness and profit, we apply the model to value evaluation. The results show that sustainability and equity are important indicators.
KEYWORDSfood security, entropy method, TOPSIS, comprehensive evaluation model
CITE THIS PAPER
Weiyao Li, Ziqi Bao, Jinyan Zhang. Research on Food Security Evaluation Model based on data implicit Distribution Mining algorithm. Agricultural & Forestry Economics and Management (2021) Vol. 4: 28-32. DOI: http://dx.doi.org/10.23977/agrfem.2021.040106
 Luo, N., Lennon, O., Liu, Y., 2021, A Conceptual Framework to Analyze Food Loss and Waste within Food Supply Chains: An Operations Management Perspective.13 (2), pp.927-927.
 Fahad, S., Sonmez, O., Saud, S., Wang, D., Wu, C., Adnan, M., Turan, V., 2021, Developing Climate Resilient Crops: Improving Global Food Security and Safety.
 Shi, X., Wei, W., Fu, Z., Gao, W., Zhang, C., Zhao, Q., Deng, F., Lu, X., 2019, Review on carbon dots in food safety applications. Talanta, 194, pp.809-821.
 Yu, X., Ge, J., Song, W., 2002, Application of Rotating Regression Analysis in Increasing Crop Yield. Mathematical Statistics and Management, 2004(2), pp.7-9.
 Mo, H., 1980, Planting density and crop yield-the quantitative relationship between yield and density and its analysis (continued). Journal of Jiangsu Agricultural College, 1980(3), pp. 12-26.