中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 海洋研究所
  3. 中国科学院海洋研究所
  4. 实验海洋生物学重点实验室
Rapid Real-Time Prediction Techniques for Ammonia and Nitrite in High-Density Shrimp Farming in Recirculating Aquaculture Systems

文献类型：期刊论文

作者Chen, Fudi4; Qiu, Tianlong1,2; Xu, Jianping2; Zhang, Jiawei3; Du, Yishuai2; Duan, Yan4; Zeng, Yihao4; Zhou, Li2; Sun, Jianming2; Sun, Ming4
刊名FISHES
出版日期2024-10-01
卷号9期号:10页码:13
关键词water quality total ammonia nitrogen nitrite nitrogen machine learning predicting model
DOI10.3390/fishes9100386
通讯作者Sun, Ming(sunming0408@163.com)
英文摘要Water quality early warning is a key aspect in industrial recirculating aquaculture systems for high-density shrimp farming. The concentrations of ammonia nitrogen and nitrite in the water significantly impact the cultured animals and are challenging to measure in real-time, posing a substantial challenge to water quality early warning technology. This study aims to collect data samples using low-cost water quality sensors during the industrial recirculating aquaculture process and to construct predictive values for ammonia nitrogen and nitrite, which are difficult to obtain through sensors in the aquaculture environment, using data prediction techniques. This study employs various machine learning algorithms, including General Regression Neural Network (GRNN), Deep Belief Network (DBN), Long Short-Term Memory (LSTM), and Support Vector Machine (SVM), to build predictive models for ammonia nitrogen and nitrite. The accuracy of the models is determined by comparing the predicted values with the actual values, and the performance of the models is evaluated using Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Root Mean Square Error (RMSE) metrics. Ultimately, the optimized GRNN-based predictive model for ammonia nitrogen concentration (MAE = 0.5915, MAPE = 28.95%, RMSE = 0.7765) and the nitrite concentration predictive model (MAE = 0.1191, MAPE = 29.65%, RMSE = 0.1904) were selected. The models can be integrated into an Internet of Things system to analyze the changes in ammonia nitrogen and nitrite concentrations over time through aquaculture management and routine water quality conditions, thereby achieving the application of recirculating aquaculture system water environment early warning technology.
资助项目Liaoning Academy of Agricultural Sciences ; Liaoning Academy of Agricultural Sciences Dean Fund Program ; Dalian Excellent Young Science and Technology Talent Project ; Dalian Science and Technology Bureau[2022RJ12] ; High-level Talent Project of Liaoning Ocean and Fisheries Science Research Institute ; Liaoning Ocean and Fisheries Science Research Institute[2023RC001] ; Dalian Science and Technology Innovation Fund Project ; Dalian Outstanding Young Science and Technology Talent Project ; National Key R&D Program of China[2023YFC3108202] ; [2023BS0807] ; [2021MS0505]
WOS研究方向Fisheries ; Marine & Freshwater Biology
语种英语
WOS记录号WOS:001341883200001
出版者MDPI
源URL[http://ir.qdio.ac.cn/handle/337002/199555]  
专题海洋研究所_实验海洋生物学重点实验室
通讯作者Sun, Ming
作者单位1.Key Lab Breeding Biotechnol & Sustainable Aquacult, Qingdao 266071, Peoples R China
2.Chinese Acad Sci, Inst Oceanol, CAS & Shandong Prov Key Lab Expt Marine Biol, Qingdao 266071, Peoples R China
3.Guangdong Ocean Univ, Fisheries Coll, Zhanjiang 524088, Peoples R China
4.Liaoning Ocean & Fisheries Sci Res Inst, Key Lab Protect & Utilizat Aquat Germplasm Resourc, Minist Agr & Rural Affairs, Liaoning Prov Key Lab Marine Biol Resources & Ecol, Dalian 116023, Peoples R China
推荐引用方式
GB/T 7714		 Chen, Fudi,Qiu, Tianlong,Xu, Jianping,et al. Rapid Real-Time Prediction Techniques for Ammonia and Nitrite in High-Density Shrimp Farming in Recirculating Aquaculture Systems[J]. FISHES,2024,9(10):13.
APA Chen, Fudi.,Qiu, Tianlong.,Xu, Jianping.,Zhang, Jiawei.,Du, Yishuai.,...&Sun, Ming.(2024).Rapid Real-Time Prediction Techniques for Ammonia and Nitrite in High-Density Shrimp Farming in Recirculating Aquaculture Systems.FISHES,9(10),13.
MLA Chen, Fudi,et al."Rapid Real-Time Prediction Techniques for Ammonia and Nitrite in High-Density Shrimp Farming in Recirculating Aquaculture Systems".FISHES 9.10(2024):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。