数据挖掘技术在温室作物生长预测中的应用

Application of Data Mining in the Prediction of Crop Growth in the Greenhouse

随着多种农业数据的增加,人工分析数据会变得越来越难 数据挖掘是一个人机交互的、智能决策的过程 它可以从大量数据中将具有潜在应用价值的信息抽取成用户可以理解的知识 笔者采用数据控掘技术预测温室作物生长 因作物生长是时序性的,提出在时序数据库转化为关系型数据库时,运用程度词的方法来进行转换 在预测作物器官的生长时,文中提出了用数据挖掘的方法从作物生长的历史数据中寻找潜在规律来预测 通过与其他预测技术进行比较,结果发现运用数据挖掘的方法具有较高的预测精度。

With increasing amount of agriculture data, it becomes difficult to analyze the data manually. Data mining is a humanmachine interactive, intelligent decision process. It can extract useful knowledge from potentially valuable information inside large amount of data. Because the crop growths in sequence, we use the method of 'degree word' to convert the sequential database to the relational database. When predicting the organ growth, we use the datamining to find out the potential rules from the historical data during the crop growth. Comparing with other prediction techniques, the datamining method can achieve higher precision and anticipated effects.