基于多环境因素分析的猪舍温湿度预测模型  

Prediction model of temperature and humidity in pig barn based on multi-environmental factors analysis

作　　者：朱佳明 孙彬 蒲施桦[1,2] 潘学民 徐顺来 胡彬[2] 齐仁立 ZHU Jiaming;SUN Bin;PU Shihua;PAN Xuemin;XU Shunlai;HU Bin;QI Renli(Chongqing Academy of Animal Science,Chongqing 402460,China;National Center of Technology Innovation for Pigs,Chongqing 402460,China)

机构地区：[1]重庆市畜牧科学院,重庆402460 [2]国家生猪技术创新中心,重庆402460

出　　处：《华南农业大学学报》2024年第5期709-721,共13页Journal of South China Agricultural University

基　　金：“十四五”国家重点研发计划(2021YFD2000803)。

摘　　要：【目的】针对环控设备调控滞后导致的密闭猪舍内温湿度波动大问题,提出合适的多元时间序列温湿度预测模型。【方法】采用皮尔逊相关性分析确定采集到的12种环境因子的相关性,初步筛选模型的输入特征。对已筛选的输入特征归一化,消除数据尺度的影响,选取DDGCRN、长短期记忆网络、支持向量回归和随机森林模型,对模型预测结果实例验证,筛选出性能最好的模型。【结果】筛选确定了温湿度预测模型的输入特征。经对比验证,DDGCRN模型预测精度最高,其预测温度和湿度的平均绝对误差分别为0.079和0.458,均方根误差分别为0.134和0.719,平均绝对百分比误差分别为0.392%和0.675%。模型输入配置比较分析表明,过多的输入特征并不能使得模型的预测能力提高,反而可能降低,且不同类型的模型以及不同的预测目标都有不同的合适的输入特征。【结论】使用DDGCRN温湿度预测模型对舍内的温湿度变换可以起到提前警告作用,为精准控制养殖环境温湿度提供参考。【Objective】To address the significant fluctuations in temperature and humidity within enclosed pig barns caused by the lag in environmental control equipment regulation,an appropriate multi-element time series temperature and humidity prediction model is proposed.【Method】Pearson correlation analysis was employed to determine the correlation among the 12 environmental factors collected,thereby preliminarily selecting the input features for the model.The selected input features were normalized to eliminate the influence of data scale.DDGCRN,long short-term memory network,support vector regression,and random forest models were chosen.The model prediction results were validated,and the best-performing model was selected.【Result】The input features of the temperature and humidity prediction model were determined.Through comparative verification,the DDGCRN model demonstrated the highest prediction accuracy.It exhibited an average absolute error of 0.079 and 0.458 for temperature and humidity predictions respectively,with a root mean square error of 0.134 and 0.719,and an average absolute percentage error of 0.392%and 0.675%.The comparative analysis of model input configurations revealed that an excessive number of input features might not improve the predictive ability of the model and could potentially decrease it.Additionally,different types of models and different prediction targets required different suitable input features.【Conclusion】The use of the DDGCRN temperature and humidity prediction model can provide early warning of temperature and humidity changes within the barns,thereby offering valuable insights for precise control of temperature and humidity in breeding environment.

关 键 词：多环境因素 密闭猪舍 温湿度 预测模型 相关性分析 

分 类 号：S818.9[农业科学—畜牧学] S828[农业科学—畜牧兽医]