基于粒子群优化算法和长短时记忆神经网络的蟹塘溶解氧预测  

Prediction model of dissolved oxygen in Chinese mitten crab ponds based on particle swarm optimization algorithm and long short-term memory neural networks

作　　者：任妮[1] 鲍彤 刘杨[1] 荀广连[1] 蒋永年 REN Ni;BAO Tong;LIU Yang;XUN Guang-lian;JIANG Yong-nian(Institute of Agricultural Information,Jiangsu Academy of Agricultural Sciences,Nanjing 210014,China;Jiangsu Zhongnong Internet of Things Technology Co.,Ltd.,Yixing 214200,China)

机构地区：[1]江苏省农业科学院农业信息研究所,江苏南京210014 [2]江苏中农物联网科技有限公司,江苏宜兴214200

出　　处：《江苏农业学报》2021年第2期426-434,共9页Jiangsu Journal of Agricultural Sciences

基　　金：江苏省农业科技自主创新基金项目[CX(19)1003]

摘　　要：为准确预测蟹塘溶解氧质量浓度,及时掌握溶解氧质量浓度的变化趋势,提前采取防控措施从而降低河蟹养殖风险,提出了一种基于粒子群优化算法(PSO)和长短时记忆神经网络(LSTM)的蟹塘溶解氧质量浓度预测模型,采用PSO算法优化LSTM模型参数后对蟹塘溶解氧质量浓度进行预测。结果表明,PSO-LSTM模型不仅整体优于ARIMA模型,相较于其他LSTM模型也有更高的预测精度,在连续10个时间点的预测中相比于LDO-LSTM、LSTM和ARIMA模型平均百分误差分别降低了2.55%、1.891%和4.055%。说明PSO-LSTM模型在蟹塘溶解氧质量浓度预测中具有良好的准确性和稳定性,可以为河蟹养殖中水质精准预测与调控提供参考。To predict the mass concentration of dissolved oxygen in Chinese mitten crab ponds accurately,grasp the changing trend of the mass concentration of dissolved oxygen timely and take preventive and control measures in advance to reduce the risk in Chinese mitten crab culturing,a model for predicting the mass concentration of dissolved oxygen in Chinese mitten crab ponds based on particle swarm optimization(PSO)and long short-term memory(LSTM)neural networks was proposed.The mass concentration of dissolved oxygen in Chinese mitten crab ponds was predicted after optimizing LSTM model parameters by PSO algorithm.The results showed that the PSO-LSTM model was not only superior to the ARIMA model,but also had higher prediction accuracy compared with other LSTM models.In the predictions at 10 consecutive time points,the average percentage error of the PSO-LSTM model reduced by 2.55%,1.891%and 4.055%respectively,compared with the LDO-LSTM,LSTM and ARIMA models.It can be seen that the PSO-LSTM model has good accuracy and stability in the prediction of the mass concentration of dissolved oxygen in Chinese mitten crab ponds,and can provide a reference for accurate prediction and regulation of water quality in Chinese mitten crab culturing.

关 键 词：溶解氧预测 河蟹养殖 粒子群优化算法 长短时记忆神经网络 

分 类 号：S126[农业科学—农业基础科学]