摘要
应用数据挖掘中关联规则的Apriori算法对玉米产量信息进行数据分析。利用最小支持度和最小置信度挖掘出频繁项集,从而寻找其中存在的关系和规则。挖掘的信息为:玉米生育期内降水量高,平均气温高,则产量高;反之,平均气温偏低,总降水量偏低,则产量低,十分可信。
The data analysis of corn yield information was analyzed through the application of Apriori algorithm of association rules in data mining. The minimum support and minimum confidence were used to dig frequent itemset mining, so as to find the existing relationships and rules. Mining information was as follows, during the growing period of the corn, if precipitation and average temperature were high, the corn yield would be high; conversely, the corn yield would be low, the results was very credible.
出处
《湖北农业科学》
2016年第3期736-739,共4页
Hubei Agricultural Sciences
基金
新疆南疆农业信息化研究中心项目(TSAI201404)
新疆生产建设兵团塔里木畜牧科技重点实验室开放课题(HS2014010)
