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GM (1, N) model is one of the grey prediction models considering the influence of many factors. This paper improves GM (1, N) model and constructs PSO-GM (1, N) model. Firstly, Lasso method is used to select the influencing factors, then the priority of influencing factors and the value of parameter N in GM (1, N) model are determined, and finally PSO method is used to optimize GM (1, N) model. Taking the vegetable supply in Henan Province as the research object, this paper makes an empirical test by using PSO-GM (1, N) model. The results show that the key factors affecting the vegetable supply in Henan Province are the number of rural employees, highway mileage, and application of pesticide. The vegetable supply in Henan Province will continue to show a steady growth trend in the next three years.

In order to explore the deep-seated reasons affecting the development of vegetable circulation in Henan Province, combined with the panel data of Henan Province from 2014 to 2019, this paper first makes a static analysis on the vegetable circulation efficiency in Henan Province by using DEA method. Second, the Malmquist method is used to establish the total factor productivity evaluation model of vegetable circulation in Henan Province, and the dynamic analysis is carried out. The analysis results show that the main problem in the development of vegetable circulation in Henan Province is the low level of management and technology. Then, GM(1, N) model is established to further analyze the specific factors affecting the vegetable circulation efficiency in Henan Province. Finally, some reasonable suggestions are put forward for the development of vegetable circulation in Henan Province.

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