基于大数据的玉米田四代棉铃虫发生量的预测模型

Forecasting model for the fourth generation of cotton bollworm in corn fields based on big data

提出了一种基于支持向量机的预测模型。根据山东省1999-2013年玉米田第四代棉铃虫发生程度采集的数据,采用支持向量回归(SVR)算法,构建了玉米田第四代棉铃虫发生程度与其关联因子间的非线性关系模型,并对该方法进行了测试与分析。结果表明,由SVR预测模型得到的预测发生量与实际发生量基本一致,预测的平均绝对百分比误差为4.36%,预测值与实际值的相关系数为0.960 6,为玉米田第四代棉铃虫的有效防控提供了科学指导。

The monitoring and forecasting model was put forward based on support vector machine program. According to the data collection of the fourth generation occurrence degree of the corn bollworm in Shandong province from 1999 to 2013, the support vector regression（SVR） method was adopted to build the nonlinear correlation model between the occurrence degree of the fourth generation bollworm and the associated factors. The method and the model were tested and analyzed. The results showed that the SVR forecasting model for prediction was almost in accord with the actual insect occurrence situation. The mean absolute percentage error was 4.36%, and the actual and estimated value of the correlation coefficient was 0.960 6. It could provide effective and accurate guidance to the cotton bollworm control in corn fields.