郑州大学学报（理学版）2026，Vol.58Issue(1)：78-86,9.DOI:10.13705/j.issn.1671-6841.2024109
Informer-LSTM融合算法在蓝莓基质温湿度预测中的研究与应用
Research and Application of Informer-LSTM Fusion Algorithm in Temperature and Humidity Prediction of Blueberry Substrate
摘要
Abstract
To predict the temperature and humidity changes of blueberry substrate in greenhouses accu-rately,a prediction method combined Informer-LSTM algorithms was proposed for blueberry substrate temperature and humidity.Taking on-site environmental data from blueberry greenhouses as the research object,the LSTM algorithm captured the dependent relationships of time series data.It was combined with self-attention mechanisms to dynamically adjust attention weights.It enabled the model to focus on both its own attention features and LSTM features simultaneously,and the model′s memory capacity was enhanced.After initial sequence generation,the LSTM algorithm was again applied to correct the short-term attention of the model,improving its reaction speed.Experimental results demonstrated that the In-former-LSTM prediction model showed significant advantages in terms of prediction accuracy,robustness,and response speed.When sequential input data such as temperature and humidity changes significantly,the dynamic pattern changes within short-term input data were captured quickly.This model had strong practical value for assisting human decision-making and achieving intelligent control in smart greenhouse management.关键词
智慧农业/温室蓝莓/Informer模型/LSTM模型/温湿度预测Key words
smart agriculture/greenhouse blueberries/Informer model/LSTM model/temperature and humidity prediction分类
信息技术与安全科学引用本文复制引用
胡玲艳,陈鹏宇,郭占俊,徐国辉,秦山,付康,盖荣丽,汪祖民,张雨萌..Informer-LSTM融合算法在蓝莓基质温湿度预测中的研究与应用[J].郑州大学学报（理学版）,2026,58(1):78-86,9.基金项目
辽宁省科技计划重点项目(2022020655-JH1/109) （2022020655-JH1/109）
大连市科技创新基金项目(2022JJ12SN052) （2022JJ12SN052）
