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Sustainable Food System for No-Hunger

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DOI: 10.23977/jaip.2020.040208 | Downloads: 17 | Views: 908


Mingquan Wang 1, Yuting Du 1, Daolong Zhang 1


1 Nanjing University of Information Science and Technology, School of Mathematics and Statistics, Applied Statistics, Nanjing Jiangsu, 210044, China

Corresponding Author

Mingquan Wang


Poverty and hunger have been a hard nut to crack throughout the world even in sections that developed well. What’s worse, environment abuse makes tackling the problem of hunger more challenging and demanding for certain countries. Therefore, it is high time for us to take Sustainability and Equity into account and change the current food system. In task 1, for the sake of numeric measurement of the food system change in response to the priority of Sustainability and Equity, we introduce the RAP-RFS coupling model including the stability estimation based on the reprioritized food system (RFS) evaluation model, and the reprioritization of the food system agricultural time-varying autoregression with stochastic volatility was introduced to calculate the impulse response to the agricultural policy (RAP) which could evaluate the efficiency of the optimized food system. The result shows, the mid-term impulse response show results inferior to the long-term response, and the longer the policy period lasts, the more negative impulse response to the agricultural policy, that is, the optimized food system works under the influence of agricultural policy. As for the RAP model, first, 6 indicators concerning 4 aspects are selected primarily to build the food system. Then entropy weighted method (EWM) is used to calculate the weight of each indicators and identify the stability. Finally, we select the GHG indicator which has high correlation with sustainability to calculate the comprehensive score, when it reaches the sustainable level 90, it will cost 3 years to achieve in 2024.


Food system, Tvp-var, Ewm, Svm, Arima


Mingquan Wang, Yuting Du, Daolong Zhang. Sustainable Food System for No-Hunger. Journal of Artificial Intelligence Practice (2021) Vol. 4: 43-49. DOI:


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