摘要
针对小样本数据下氨氮浓度模型预测精度不高、收敛速度较慢的问题,采用长短期记忆网络(long short-term memory,LSTM)建立氨氮浓度预测模型,并利用贝叶斯优化算法和元学习机制对模型进行优化。其中贝叶斯优化算法用来优化预测模型的超参数,同时给出模型参数的初始值,再使用Meta-LSTM算法学习模型梯度并允许优化器之间进行参数共享和更新,最终实现对氨氮浓度预测模型的优化。将该方法与LSTM、GRU和RNN模型进行对比试验,结果显示,研究所建模型对氨氮浓度预测的均方根误差、平均绝对误差和均方误差分别为0.0276、0.0239和0.00076,均优于其他预测模型。表明基于贝叶斯和元学习的氨氮浓度预测模型对小样本数据建模有效,可以实现网络快速收敛,精度满足水产养殖中氨氮浓度预测需求。
To address the issues of low prediction accuracy and slow convergence rate of ammonia nitrogen concentration model under small sample data,a method of establishing ammonia nitrogen concentration prediction model by using long short-term memory(LSTM)and optimizing the model by using Bayesian optimization algorithm and Meta-learning mechanism was proposed.The Bayesian optimization algorithm was used to optimize the superparameters of the prediction model,and the initial values of the model parameters were given.Then the Meta-LSTM algorithm was used to learn the model gradient and allow the parameter sharing and updating among the optimizers,and finally the optimization of the prediction model of ammonia nitrogen concentration was realized.Compared with LSTM,GRU and RNN models,the result shows that the root-mean-square error,mean absolute error and mean square error of the proposed model are 0.0276,0.0239 and 0.00076,respectively,which are better than other prediction models.It is further indicated that the prediction model of ammonia nitrogen concentration based on Bayesian and Meta-learning is effective for modeling small sample data,and can achieve convergence in rapid training.The accuracy of the model meets the prediction requirements of ammonia nitrogen concentration for aquaculture.
作者
刘懿纬
王魏
张淑雨
孙俊洋
李双双
LIU Yiwei;WANG Wei;ZHANG Shuyu;SUN Junyang;LI Shuangshuang(School of Information Engineering,Dalian Ocean University/Key Laboratory of Environment Controlled Aquaculture,Ministry of Education,Dalian 116023,China;Dalian Xinyulong Marine Biological Seed Technology Co.Ltd.,Dalian 116000,China)
出处
《华中农业大学学报》
CAS
CSCD
北大核心
2023年第4期236-243,共8页
Journal of Huazhong Agricultural University
基金
设施渔业教育部重点实验室(大连海洋大学)开放课题(202314)
辽宁省教育厅青年科技人才“育苗”项目(QL201912)。
关键词
贝叶斯优化
氨氮浓度预测
Meta-LSTM
元学习
Bayesian optimization
ammonia nitrogen concentration prediction
Meta-LSTM
Metalearning
