气象研究与应用2024，Vol.45Issue(1)：102-107,6.DOI:10.19849/j.cnki.CN45-1356/P.2024.1.17
基于决策树的水稻病虫害发生程度预测模型
A prediction model for the occurrence degree of rice diseases and pests based on decision tree algorithm:A case study in Wuhu
摘要
Abstract
Based on the C5.0 decision tree algorithm,a long-term prediction model for the occurrence of rice diseases and pests using atmospheric circulation and sea surface temperature(SST)index as predictive factors was constructed using the occurrence of seven types of rice pests and diseases and planting area data of Wuhu City from 1988 to 2022,and the monthly atmospheric circulation and SST index of National Climate Centre(NCC).The results show that these models can effectively predict the occurrence degree of various rice diseases and pests in Wuhu City in the next year.The average predicting accuracy of the occurrence degree of seven diseases and pests in 2022 is 85.7%,which provides an effective and practical method for predicting the occurrence degree of rice diseases and pests.关键词
C5.0决策树算法/水稻病虫害发生程度/预测模型/大气环流和海温指数Key words
C5.0 decision tree algorithm/occurrence degree of rice pests and diseases/prediction model/atmospheric circulation and sea surface temperature index分类
农业科技引用本文复制引用
付伟,祝玉青,司红君,邹莹瑾..基于决策树的水稻病虫害发生程度预测模型[J].气象研究与应用,2024,45(1):102-107,6.基金项目
国家重点研发计划项目(2018YFD0300905)、科技助力经济2020重点专项气象行业项目(KJZLJJ202002) （2018YFD0300905）
