Intelligent feeding technique based on predicting shrimp growth in recirculating aquaculture system
文献类型：期刊论文
| 作者 | Chen, Fudi1,2,3 ; Sun, Ming1,2,3; Du, Yishuai2,3; Xu, Jianping2,3; Zhou, Li2,3; Qiu, Tianlong2,3; Sun, Jianming2,3
|
| 刊名 | AQUACULTURE RESEARCH
 |
| 出版日期 | 2022-06-22 |
| 页码 | 13 |
| ISSN号 | 1355-557X |
| 关键词 | Litopenaeus vannamei precise feeding predicting model shrimp biomass |
| DOI | 10.1111/are.15938 |
| 通讯作者 | Sun, Jianming(jianming_sun@outlook.com) |
| 英文摘要 | Precise feeding in the recirculating aquaculture mode is a critical scientific problem that urgently needs a solution. This study aimed to develop an intelligent feeding technique in a recirculating aquaculture system for rearing Litopenaeus vannamei. The core of the intelligent feeding technique is the shrimp biomass prediction model. Accurate prediction of shrimp biomass could determine the appropriate feeding amount and ensure stable water quality. The data-driven prediction model was developed based on water quality indicators and aquaculture management data collected during shrimp rearing. Multiple linear regression, artificial neural networks and a support vector machine (SVM) were introduced to develop the shrimp biomass predicting model. Results showed that the SVM model gave the lowest root mean square error (0.6500), mean absolute error (0.4368) and mean absolute percentage error (3.70%), as well as the highest accuracy (90.91%). By analysing the predictive ability of the machine learning models, it was determined that the SVM model was the optimal model for predicting biomass. The intelligent feeding machine can apply the optimal model to calculate the shrimp biomass and determine the appropriate feeding amount by reading the sensors in real time. |
| 资助项目 | China Postdoctoral Science Foundation[2021M693212] ; Ministry of Science and Technology of the People's Republic of China[2017YFE0118300] ; Ministry of Science and Technology of the People's Republic of China[2019YFD0900502] ; Ministry of Science and Technology of the People's Republic of China[2019YFD0900800] |
| WOS研究方向 | Fisheries |
| 语种 | 英语 |
| 出版者 | WILEY |
| WOS记录号 | WOS:000814051300001 |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/179604]  |
| 专题 | 海洋研究所_实验海洋生物学重点实验室 |
| 通讯作者 | Sun, Jianming |
| 作者单位 | 1.Liaoning Ocean & Fisheries Sci Res Inst, Liaoning Prov Key Lab Marine Biol Resources & Eco, Dalian Key Lab Conservat Fishery Resources, Dalian, Peoples R China 2.Qingdao Natl Lab Marine Sci & Technol, Lab Marine Biol & Biotechnol, Qingdao, Peoples R China 3.Chinese Acad Sci, Ctr Ocean Megasci, Inst Oceanol, CAS & Shandong Prov Key Lab Expt Marine Biol, Qingdao 266071, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Fudi,Sun, Ming,Du, Yishuai,et al. Intelligent feeding technique based on predicting shrimp growth in recirculating aquaculture system[J]. AQUACULTURE RESEARCH,2022:13. |
| APA | Chen, Fudi.,Sun, Ming.,Du, Yishuai.,Xu, Jianping.,Zhou, Li.,...&Sun, Jianming.(2022).Intelligent feeding technique based on predicting shrimp growth in recirculating aquaculture system.AQUACULTURE RESEARCH,13. |
| MLA | Chen, Fudi,et al."Intelligent feeding technique based on predicting shrimp growth in recirculating aquaculture system".AQUACULTURE RESEARCH (2022):13. |
入库方式： OAI收割
来源：海洋研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。