智慧农业（中英文）2025，Vol.7Issue(3)：143-159,17.DOI:10.12133/j.smartag.SA202502015
基于改进VMD-LSTM的作物冠层温度动态预测模型
Dynamic Prediction Model of Crop Canopy Temperature Based on VMD-LSTM
摘要
Abstract
[Objective]Accurate prediction of crop canopy temperature is essential for comprehensively assessing crop growth status and guiding agricultural production.This study focuses on kiwifruit and grapes to address the challenges in accurately predicting crop canopy temperature.[Methods]A dynamic prediction model for crop canopy temperature was developed based on Long Short-Term Memory(LSTM),Variational Mode Decomposition(VMD),and the Rime Ice Mor-phology-based Optimization Algorithm(RIME)optimization algorithm,named RIME-VMD-RIME-LSTM(RIME2-VMD-LSTM).Firstly,crop canopy temperature data were collected by an inspection robot suspended on a cableway.Secondly,through the performance of multiple pre-test experiments,VMD-LSTM was selected as the base model.To reduce cross-interference between different frequency components of VMD,the K-means clustering algorithm was applied to cluster the sample entropy of each component,reconstructing them into new components.Finally,the RIME optimization algo-rithm was utilized to optimize the parameters of VMD and LSTM,enhancing the model's prediction accuracy.[Results and Discussions]The experimental results demonstrated that the proposed model achieved lower Root Mean Square Er-ror(RMSE)and Mean Absolute Error(MAE)(0.360 1 and 0.254 3℃,respectively)in modeling different noise environ-ments than the comparator model.Furthermore,the R2 value reached a maximum of 0.994 7.[Conclusions]This model provides a feasible method for dynamically predicting crop canopy temperature and offers data support for assessing crop growth status in agricultural parks.关键词
冠层温度/温度预测/长短期记忆网络/雾凇优化算法/变分模态分解Key words
canopy temperature/temperature prediction/LSTM/RIME/VMD分类
信息技术与安全科学引用本文复制引用
王毓玺,黄铝文,段小琳..基于改进VMD-LSTM的作物冠层温度动态预测模型[J].智慧农业（中英文）,2025,7(3):143-159,17.基金项目
National Key R&D Program of China(2020YFD1100601) 国家重点研发计划项目(2020YFD1100601) （2020YFD1100601）
