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The measurement of the agricultural economic cycle and its synergy analysis are of great significance for the formulation of agricultural macroeconomic policies. When the traditional methods are used to analyze the main factors affecting the synergy of agricultural economic cycle fluctuations, almost all of them use the correlation coefficient or the degree of agreement to express the degree of economic cycle synergy. It is impossible to accurately evaluate the degree of synergy of economic cycle fluctuations. To solve this problem, a quantitative calculation model of agricultural economic cycle synergy evaluation based on the ant colony algorithm is proposed. On the basis of the collected monthly data of agricultural economic operation indicators, a prosperity index that comprehensively reflects the development of agricultural economy is constructed. The law of economic prosperity cycle fluctuation is analyzed according to economic prosperity index, and HP filtering is utilized to decompose the trend fluctuations of the economic time series of various industries and obtain the fluctuation components. The ant colony algorithm is utilized to optimize the spearman correlation analysis method, and the correlation analysis of the wave components is carried out. The Fisher-z conversion is performed on the optimal Spearman correlation coefficient obtained by the optimization. The transformed results represent the degree of economic cycle synergy, considering the geographical distance, economic space spillover, fiscal policy synergy, regional income gap and geographical neighbors, a quantitative calculation model for agricultural economic cycle synergy evaluation is established. The results show that the agricultural economic cycle has a certain spatial correlation, and will expand the agricultural economic fluctuations and form the cycle synergy through the periodic space overflow.

Synergy analysis of agricultural economic cycle fluctuation based on ant colony algorithm