In order to comprehensively and objectively analyze the development level of agricultural circular economy and accurately predict the development trend of agricultural circular economy, a prediction model for the growth trend of agricultural circular economy based on GP algorithm was studied. On this basis, an evaluation system for the development of agricultural circular economy has been established from the perspectives of economic and social development, resource reduction and investment, resource recycling, resource environment and security, and population system. The kernel principal component analysis method was used to reduce the dimensionality of the indicator system for the development of agricultural circular economy, and the reduced dimension of agricultural circular economy development index is set as the input of GP algorithm. The GP algorithm is optimized by fixed structure, multi-population and coefficient climbing method. Finally, the GP algorithm is applied to predict the development trend of agricultural circular economy. The results indicate that the model proposed in this article can effectively predict the agricultural circular economy, which is of great significance for promoting the further development of the agricultural circular economy.
GP algorithm, agricultural cycle, economic development trend, trend prediction model, index system, kernel principal component analysis
YIN, Yue and NING, Weidong
"Forecast model of agricultural circular economy development trend based on GP algorithm,"
Turkish Journal of Agriculture and Forestry: Vol. 48:
1, Article 5.
Available at: https://journals.tubitak.gov.tr/agriculture/vol48/iss1/5