摘要
目的:针对母猪妊娠期饲喂问题,对妊娠母猪饲喂量进行预测,以精确控制妊娠母猪所需要的饲料量,有助于母猪精准饲喂,节约养殖成本。方法:结合ARIMA和LSTM算法的各自优势,利用融合ARIMA和LSTM的ARIMA-LSTM优化算法,对妊娠期母猪饲喂量进行精准预测,以控制智能饲喂器精准下料。结果:ARIMA-LSTM优化算法对母猪饲喂量的预测精度最高,相比ARIMA和LSTM算法,均方根误差分别降低48.74%和17.22%,平均绝对偏差分别降低48.70%和27.37%。结论:ARIMA-LSTM优化算法能够提高母猪妊娠期饲喂量的预测精度,能够控制智能饲喂器精准下料,为妊娠母猪饲喂量预测提供较好的依据。
Objective:To predict the feeding amount of pregnant sows,in order to accurately control the amount of feed required for pregnant sows,and to help feed sows accurately and save breeding costs.Methods:By combining the advantages of ARIMA and LSTM algorithms,and utilizing the ARIMA-LSTM optimization algorithm that integrated ARIMA and LSTM,the feeding amount of pregnant sows was accurately predicted to control the precise feeding of intelligent feeders.Results:The ARIMA-LSTM optimization algorithm has been experimentally verified to have the highest prediction accuracy for sow feeding volume.Compared with ARIMA and LSTM algorithms,the root mean square error has been reduced by 48.74%and 17.22%,respectively,and the average absolute deviation has been reduced by 48.70%and 27.37%,respectively.Conclusion:The ARIMA-LSTM optimization algorithm used in this article improved the prediction accuracy of feeding amount during pregnant sows,and could control the precise feeding of intelligent feeders,providing a good basis for predicting feeding amount in pregnant sows.
作者
岳宝昌
樊晓宇
凌丽
谭飞飞
王洋
任国栋
YUE Baochang;FAN Xiaoyu;LING Li;TAN Feifei;WANG Yang;REN Guodong(College of Mechanical Engineering,Anhui Science and Technology University,Fengyang 233100,China;School of Electrical and Electronic Engineering,Anhui Science and Technology University,Bengbu 233030,China;Bengbu Yi'ai Electronic Technology Co.,Ltd.,Bengbu 233000,China)
出处
《安徽科技学院学报》
2024年第4期110-116,共7页
Journal of Anhui Science and Technology University
基金
安徽省高校自然科学研究项目(2022AH051633)
安徽省农业物质技术装备领域揭榜挂帅项目(S202320230906020001)
蚌埠市科技计划项目(2022gx10)
安徽科技学院人才稳定项目(HCWD202001)
安徽科技学院科研发展基金项目(FZ220116)。
作者简介
岳宝昌(1996-),男,安徽阜阳人,硕士研究生,主要从事智能农业装备研究,E-mail:ahstu88xb@163.com;通信作者:樊晓宇,副教授,E-mail:fanxy@ahstu.edu.cn。
