Grassland Ecological Association Rules Mining Based on Improved Apriori Algorithm
To further explore the causes of grassland ecological formation,based on the grassland ecological footprint model,the K-means clustering algorithm is used to hierarchically identify grassland ecology and related indicators,and the Apriori im-proved algorithm is used for data mining to analyze the causes of grassland ecology.The experimental results show that the improved algorithm has improved both efficiency and effectiveness.According to the interpretation of association rules,in terms of economic factors,the growth of per capita GDP and the expansion of the proportion of employment in the tertiary industry stimulate the con-sumption of grassland resources by animal husbandry.In terms of social and natural factors,the large population,low rainfall,and geographical differences in agricultural and pastoral areas can all have inhibitory effects on grassland ecology.
万方数据
维普
