An optimization method for environmental parameters in factory farming of juvenile spotted knifejaw based on deep learning and dual-objective optimization
Year: 2025
Type: article
Language: en
Topic: Water Quality Monitoring Technologies
Authors and affiliations:
raw_author_name: Yihan Yin
raw_affiliation_strings: Engineering and Technology Research Center for Internet of Things in Agriculture, China Agricultural University, Beijing, 10083, China
Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, Beijing, 10083, China
National Innovation Center for Digital Fishery, China Agricultural University, Beijing, 10083, China
State Key Laboratory of Efficient Utilization of Agricultural Water Resources, China Agricultural University, Beijing, 100083, China
raw_author_name: Xueqian Sun
raw_affiliation_strings: Engineering and Technology Research Center for Internet of Things in Agriculture, China Agricultural University, Beijing, 10083, China
Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, Beijing, 10083, China
National Innovation Center for Digital Fishery, China Agricultural University, Beijing, 10083, China
State Key Laboratory of Efficient Utilization of Agricultural Water Resources, China Agricultural University, Beijing, 100083, China
raw_author_name: Fang Ji
raw_affiliation_strings: College of Information and Electrical Engineering, China Agricultural University, Beijing, 10083, China
Engineering and Technology Research Center for Internet of Things in Agriculture, China Agricultural University, Beijing, 10083, China
Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, Beijing, 10083, China
National Innovation Center for Digital Fishery, China Agricultural University, Beijing, 10083, China
State Key Laboratory of Efficient Utilization of Agricultural Water Resources, China Agricultural University, Beijing, 100083, China
raw_author_name: Daoliang Li
raw_affiliation_strings: College of Information and Electrical Engineering, China Agricultural University, Beijing, 10083, China
Engineering and Technology Research Center for Internet of Things in Agriculture, China Agricultural University, Beijing, 10083, China
Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, Beijing, 10083, China
National Innovation Center for Digital Fishery, China Agricultural University, Beijing, 10083, China
State Key Laboratory of Efficient Utilization of Agricultural Water Resources, China Agricultural University, Beijing, 100083, China
raw_author_name: Yang Wang
raw_affiliation_strings: College of Information and Electrical Engineering, China Agricultural University, Beijing, 10083, China
Engineering and Technology Research Center for Internet of Things in Agriculture, China Agricultural University, Beijing, 10083, China
Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, Beijing, 10083, China
National Innovation Center for Digital Fishery, China Agricultural University, Beijing, 10083, China
State Key Laboratory of Efficient Utilization of Agricultural Water Resources, China Agricultural University, Beijing, 100083, China