Simulation optimization of economic benefit model of agricultural industry based on DEA model

Li Jiang

doi:10.1117/12.2672774

28 March 2023 Simulation optimization of economic benefit model of agricultural industry based on DEA model

Li Jiang

Proceedings Volume 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022); 1259748 (2023) https://doi.org/10.1117/12.2672774
Event: Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 2022, Nanjing, China

Abstract

With the continuous reform of the economic system, structural adjustment is the general trend. The rationalization of the structure is of great practical significance to the improvement of the agricultural economic level and is an important link in the rapid growth of the national economy. While the growth of agriculture is constantly developing towards modernization, scale and intensification, it requires the continuous improvement of agricultural production efficiency. Starting with the influence of adjusting agricultural structure on improving agricultural economic benefits, this article assesses the economic benefits of agricultural industry by using Data Envelopment Analysis (DEA) model, and analyzes the measures of adjusting agricultural structure, which provides the basis for the rational allocation of agricultural production factors and the optimal adjustment of planting structure. The improvement of agricultural production efficiency is an important way to enhance agricultural competitiveness, raise farmers' income level and improve farmers' living conditions. We must attach importance to the growth of modern agriculture and characteristic agriculture with innovation as the core content.

Citation Download Citation

Li Jiang "Simulation optimization of economic benefit model of agricultural industry based on DEA model", Proc. SPIE 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 1259748 (28 March 2023); https://doi.org/10.1117/12.2672774

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