四川农业大学学报 ›› 2006, Vol. 24 ›› Issue (01): 37-39,60.doi: 10.16036/j.issn.1000-2650.2006.01.008

• 研究论文 • 上一篇    下一篇

稻飞虱发生程度的神经网络模型拟合研究

王海建1,2, 杨茂发2, 李庆1, 杨群芳1, 李子忠2   

  1. 1. 四川农业大学 农学院, 四川 雅安 625014;
    2. 贵州大学 昆虫研究所, 贵阳 550025
  • 收稿日期:2005-12-14 出版日期:2006-03-31 发布日期:2017-03-04
  • 基金资助:
    "九五"科技攻关项目:贵州省水稻重大病虫草害综合治理及应用技术研究;贵州省省长专项基金项目:贵州省稻瘟病、稻飞虱综合治理技术研究

Studies on Planthoppers Occurrence Degree with the Artificial Neural Network

WANG Hai-jian1,2, YANG Mao-fa2, LI Qing1, YANG Qun-fang1, LI Zi-zhong2   

  1. 1. College of Agriculture, Sichuan Agricultural University, Yaan 625014, Sichuan, China;
    2. Institute of Entomology, Guizhou University, Guiyang 550025, Guizhou, China
  • Received:2005-12-14 Online:2006-03-31 Published:2017-03-04

摘要: 根据贵州省三都县和锦屏县1981~1998年稻飞虱发生的历史资料和气象资料,应用神经网络模型方法对稻飞虱的发生程度作了预测拟合。结果表明,三都县白背飞虱(Sogatella furcifera)的历史符合率达到100%,对1996、1997、19983年拟合,1996和1997两年与实际发生相符,1998年与实际发生情况基本相符;褐飞虱(Nilaparvata lugens)历史符合率93.33%,对1996、1997、1998年拟合,结果全部符合实际发生。锦屏县白背飞虱和褐飞虱历史符合率均达到100%,对1992~19965年拟合,白背飞虱和褐飞虱的准确率分别达到100%和80%。该研究结果表明神经网络在稻飞虱发生程度的预测上具有较好的应用前景。

关键词: 稻飞虱, 神经网络模型, 模型拟合

Abstract: According to the historical data of rice planthoppers' outbreak and meteorology in Sandu County and Jinping County, Guizhou Province, the author applied the Artificial Neural Network(ANN) to fitting the occurrence of rice planthoppers to test the coincidence between the fitting and its real happening. The results show:In Sandu, the history coincidence rate of Nilaparvata lugens Stal and Sogatella furcifera(Horvath) is 93.33%, 100%, respectively, based on fifteen years' data; the fitting of BP-ANNS has a high coincidence with their happening in three years. In Jinping, the history coincidence rate of both species is 100% based on ten years' data; and the BP-ANN can fit Nilaparvata lugens Stal at a high degree and Sogatella furcifera(Horvath) perfectly in five years. The BP-ANNS is a potential method at the recurrence of rice plant hoppers' outbreak.

Key words: rice planthoppers, Artificial Neural Network, model fitting

中图分类号: 

  • S435.112+.3