农业机械学报2026，Vol.57Issue(5)：417-426,10.DOI:10.6041/j.issn.1000-1298.2026.05.039
基于WT-SSA-LSTM的羊舍PM2.5浓度预测模型研究
PM2.5 Concentration Prediction Model in Sheep House Based on WT-SSA-LSTM
摘要
Abstract
In intensive sheep farming,the lack and backwardness of environmental management technologies are key factors contributing to the deterioration of sheep house environments.Accurately predicting changes in sheep house environmental parameters are crucial for ensuring the healthy growth of sheep and improving the economic benefits of the sheep farming industry.To accurately understand the PM2.5 concentration patterns within sheep houses,the wavelet transform(WT)was used to decompose and reconstruct sheep house environmental parameter data to eliminate data noise.The sparrow search algorithm(SSA)was then used to optimize the number of hidden layer neurons,learning rate,and batch size of the LSTM model.This approach also adjusted the input model parameters to avoid randomness in parameter selection and further improve model performance.Experimental results showed that the WT-SSA-LSTM model outperformed other prediction models in all metrics,with MAE,RMSE,MSE,NRMSE,and R2 reaching 0.3497 μg/m3,0.6004 μg/m3,0.3605 μg2/m6,0.0057,and 0.9981,respectively.This demonstrated the high accuracy and stability of the proposed WT-SSA-LSTM prediction model,effectively providing guidance for monitoring and regulating PM2.5 levels in intensive sheep farming facilities.Future applications suggested that the proposed model could be applied to environmental parameter prediction for other animal housing applications,such as piggeries and cattle sheds.关键词
羊舍/PM2.5浓度预测/小波变换降噪/麻雀搜索算法/长短时记忆网络Key words
sheep house/PM2.5 concentration prediction/wavelet transform noise reduction/sparrow search algorithm/long short-term memory network分类
信息技术与安全科学引用本文复制引用
周冰,董佳琦,邢赫,陈苑冰,王裕莞,刘双印..基于WT-SSA-LSTM的羊舍PM2.5浓度预测模型研究[J].农业机械学报,2026,57(5):417-426,10.基金项目
国家自然科学基金项目(62373390)、广东省自然科学基金重点项目(2022B1515120059)、广州市科技计划项目(2023E04J1238、2023E04J1239)、新疆维吾尔自治区重大科技专项(2022A02011)、云浮市科技计划项目(2024020202、2022020303、2023020302)、2025年度广州商学院校级科研项目(2025XJYB038)和2025年度广州商学院校级教学质量与教学改革工程项目(2025ZLGC33) （62373390）
