基于LightGBM-SSA-ELM的新疆羊舍CO_(2)浓度预测

Prediction of CO_(2) Concentration in Xinjiang Breeding Environment of Mutton Sheep Based on LightGBM SSA ELM

为减少肉羊集约化养殖过程中因环境恶化产生的应激反应,精准调控CO_(2)质量浓度,提出了基于分布式梯度提升框架(LightGBM)、麻雀搜索算法(SSA)融合极限学习机(ELM)的CO_(2)质量浓度预测模型。首先利用LightGBM筛选出与CO_(2)质量浓度相关的重要特征,降低预测模型的输入维度;然后选择Sigmoid为激活函数,使用具有较强非线性处理能力的单隐含层ELM神经网络算法构建CO_(2)质量浓度预测模型;最后通过麻雀智能优化算法对ELM模型中所需要的超参数进行优化,并将优化后模型应用于新疆玛纳斯集约化肉羊养殖基地。试验结果表明,该模型预测均方根误差(RMSE)、平均绝对误差(MAE)和决定系数(R^(2))分别为0.0213 mg/L、0.0136 mg/L和0.9886,综合性能指标优于支持向量回归(SVR)、反向传播神经网络(BPNN)、长短记忆神经网络(LSTM)、门限循环单元(GRU)和LightGBM等;CO_(2)质量浓度预测曲线贴近真实曲线,具有良好的预测效果,能有效满足集约化肉羊养殖过程中CO_(2)质量浓度精准预测及调控要求。

Air quality plays an important role in mutton sheep breeding environment,in order to reduce the stress response of CO_(2) to the growth of large-scale mutton sheep and ensure the healthy growth of mutton sheep in the appropriate environment,the key is to accurately control the CO_(2) in the mutton sheep breeding environment.A CO_(2) prediction model of mutton sheep breeding environment was proposed based on light gradient boosting machine(LightGBM),sparrow search algorithm(SSA)and extreme learning machine(ELM).Firstly,LightGBM was used to screen out the important characteristics of carbon dioxide concentration and reduce the input dimension of the prediction model.Then,ELM neural network algorithm with single hidden layer with strong nonlinear processing ability was used to build the CO_(2) prediction model.Finally,through the sparrow intelligent optimization algorithm,the super parameters needed in ELM model were optimized to obtain the best prediction model.The prediction model was applied to a large-scale mutton sheep breeding base in Manas County,Changji Hui Autonomous Prefecture,Xinjiang Uygur Autonomous Region,and good prediction results were obtained.The experimental results showed that the prediction model had good prediction effect,and the root mean square error(RMSE)of ELM was higher than that of SVR,BPNN,LSTM,GRU and LightGBM.The RMSE,mean absolute error(MAE)and R^(2) were 0.0213 mg/L,0.0136 mg/L and 0.9886,respectively.The results showed that the combined model can not only achieve accurate control of carbon dioxide in sheep house,but also meet the needs of fine decision-making for mutton sheep breeding.It also can help farmers make decisions and reduce farming risks.