Apriori算法在棉花病虫害分析中的应用

为了快速准确地掌握棉花虫害发生趋势，提高虫情测报的时效性和准确性，采用Apriori算法数据挖掘关联规则，对棉花上的3种害虫棉铃虫、棉叶螨、棉蚜的发生趋势进行综合分析。通过Apriori算法寻找出了气候因素与棉花三大害虫的发生发展有密切的关系，尤其气温变化直接影响到棉花害虫的发生种类、发生期及发生量。联规则数据挖掘技术，在处理大量农业信息数据中起着非常重要的作用，Apriori算法在棉花病虫测报工作中将是一项新的技术，具有非常广泛的应用前景。

Application of Apriori Algorithm in Analysis of Cotton Disease and Insect Pest

To quickly and accurately know the trend of cotton insect pest and improve the timeliness and accuracy of forecast, we applied data mining technology using association rules in Apriori algorithm to comprehensively analyze the occurrence trend of three kinds of cotton pests including cotton bollworm, cotton spider mites and cotton aphid. The results showed that the occurrence of the three major cotton pests had a close relationship with climatic factors. In particular, the changes of temperature directly affected the species, period and amount of pest occurrence. Data mining technology using association rules plays a very important role in dealing with a large number of agricultural information data. Apriori algorithm is a new technology in forecasting cotton pest and has broad application prospect.