{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:33:00Z","timestamp":1760059980594,"version":"build-2065373602"},"reference-count":19,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2025,7,22]],"date-time":"2025-07-22T00:00:00Z","timestamp":1753142400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Open Fund Project 2024 of the Key Laboratory of Smart Farming","award":["2024-TJAULSBF-2404","24YFZCSN00200","23YFZCSN00310","2024ZY1NC004","2020YFD0900600","CARS-47","ITTMRS2021000","2023KJ004"],"award-info":[{"award-number":["2024-TJAULSBF-2404","24YFZCSN00200","23YFZCSN00310","2024ZY1NC004","2020YFD0900600","CARS-47","ITTMRS2021000","2023KJ004"]}]},{"name":"The Key Technologies R &amp; D Program of Tianjin","award":["2024-TJAULSBF-2404","24YFZCSN00200","23YFZCSN00310","2024ZY1NC004","2020YFD0900600","CARS-47","ITTMRS2021000","2023KJ004"],"award-info":[{"award-number":["2024-TJAULSBF-2404","24YFZCSN00200","23YFZCSN00310","2024ZY1NC004","2020YFD0900600","CARS-47","ITTMRS2021000","2023KJ004"]}]},{"name":"2024 Gannan Prefecture Science and Technology Plan Project","award":["2024-TJAULSBF-2404","24YFZCSN00200","23YFZCSN00310","2024ZY1NC004","2020YFD0900600","CARS-47","ITTMRS2021000","2023KJ004"],"award-info":[{"award-number":["2024-TJAULSBF-2404","24YFZCSN00200","23YFZCSN00310","2024ZY1NC004","2020YFD0900600","CARS-47","ITTMRS2021000","2023KJ004"]}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2024-TJAULSBF-2404","24YFZCSN00200","23YFZCSN00310","2024ZY1NC004","2020YFD0900600","CARS-47","ITTMRS2021000","2023KJ004"],"award-info":[{"award-number":["2024-TJAULSBF-2404","24YFZCSN00200","23YFZCSN00310","2024ZY1NC004","2020YFD0900600","CARS-47","ITTMRS2021000","2023KJ004"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the earmarked fund for CARS","award":["2024-TJAULSBF-2404","24YFZCSN00200","23YFZCSN00310","2024ZY1NC004","2020YFD0900600","CARS-47","ITTMRS2021000","2023KJ004"],"award-info":[{"award-number":["2024-TJAULSBF-2404","24YFZCSN00200","23YFZCSN00310","2024ZY1NC004","2020YFD0900600","CARS-47","ITTMRS2021000","2023KJ004"]}]},{"name":"Tianjin Mariculture Industry Technology System Innovation Team Construction Project","award":["2024-TJAULSBF-2404","24YFZCSN00200","23YFZCSN00310","2024ZY1NC004","2020YFD0900600","CARS-47","ITTMRS2021000","2023KJ004"],"award-info":[{"award-number":["2024-TJAULSBF-2404","24YFZCSN00200","23YFZCSN00310","2024ZY1NC004","2020YFD0900600","CARS-47","ITTMRS2021000","2023KJ004"]}]},{"name":"Scientific Developing Foundation of Tianjin Education Commission","award":["2024-TJAULSBF-2404","24YFZCSN00200","23YFZCSN00310","2024ZY1NC004","2020YFD0900600","CARS-47","ITTMRS2021000","2023KJ004"],"award-info":[{"award-number":["2024-TJAULSBF-2404","24YFZCSN00200","23YFZCSN00310","2024ZY1NC004","2020YFD0900600","CARS-47","ITTMRS2021000","2023KJ004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JSAN"],"abstract":"<jats:p>Traditional methods for predicting feeding amounts rely on historical data and experience but fail to account for non-linear fish growth and the influence of water quality and meteorological factors. This study presents a novel approach for sea bass feeding prediction based on Spearman + RF feature optimization and multi-scale feature fusion using a transformer model. A logistic growth curve model is used to analyze sea bass growth and establish the relationship between biomass and feeding amount. Spearman correlation analysis and random forest optimize the feature set for improved prediction accuracy. A dual-encoder structure incorporates historical feeding data and biomass along with water quality and meteorological information. Multi-scale feature fusion addresses time-scale inconsistencies between input variables The results showed that the MSE and MAE of the improved transformer model for sea bass feeding prediction were 0.42 and 0.31, respectively, which decreased by 43% in MSE and 33% in MAE compared to the traditional transformer model.<\/jats:p>","DOI":"10.3390\/jsan14040077","type":"journal-article","created":{"date-parts":[[2025,7,22]],"date-time":"2025-07-22T09:47:06Z","timestamp":1753177626000},"page":"77","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["FO-DEMST: Optimized Multi-Scale Transformer with Dual-Encoder Architecture for Feeding Amount Prediction in Sea Bass Aquaculture"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-1606-2515","authenticated-orcid":false,"given":"Hongpo","family":"Wang","sequence":"first","affiliation":[{"name":"Key Laboratory of Smart Breeding (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs (TJAU), Tianjin 300384, China"},{"name":"School of Computer and Information Engineering, Tianjin Agricultural College, Tianjin 300392, China"}]},{"given":"Qihui","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Engineering, Tianjin Agricultural College, Tianjin 300392, China"}]},{"given":"Hong","family":"Zhou","sequence":"additional","affiliation":[{"name":"Key Laboratory of Smart Breeding (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs (TJAU), Tianjin 300384, China"},{"name":"School of Computer and Information Engineering, Tianjin Agricultural College, Tianjin 300392, China"}]},{"given":"Yunchen","family":"Tian","sequence":"additional","affiliation":[{"name":"Key Laboratory of Smart Breeding (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs (TJAU), Tianjin 300384, China"},{"name":"School of Computer and Information Engineering, Tianjin Agricultural College, Tianjin 300392, China"}]},{"given":"Yongcheng","family":"Jiang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Smart Breeding (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs (TJAU), Tianjin 300384, China"},{"name":"College of Engineering and Technology, Tianjin Agricultural University, Tianjin 300384, China"}]},{"given":"Jianing","family":"Quan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Smart Breeding (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs (TJAU), Tianjin 300384, China"},{"name":"School of Computer and Information Engineering, Tianjin Agricultural College, Tianjin 300392, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,22]]},"reference":[{"key":"ref_1","unstructured":"Ministry of Agriculture and Rural Affairs of the People\u2019s Republic of China, Fisheries and Fishery Administration, National Station of Aquatic Technology Promotion, and Chinese Society of Fisheries (2023). China Fishery Statistical Yearbook 2023, China Agriculture Press."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1111\/raq.12202","article-title":"Improving feed efficiency in fish using selective breeding: A review","volume":"10","author":"Komen","year":"2018","journal-title":"Rev. Aquac."},{"key":"ref_3","unstructured":"Wang, Z., and Lian, J. (1999). Analysis of factors affecting the growth of fish in offshore cage farming\u2014Application of Interpretive Structural Modeling Method. J. Fish. Sci., 300\u2013303."},{"key":"ref_4","first-page":"23","article-title":"A study on the early growth and development of largemouth bass","volume":"26","author":"He","year":"2011","journal-title":"J. Dalian Ocean Univ."},{"key":"ref_5","first-page":"72","article-title":"Growth\u2014Related analysis and model construction of Nile tilapia","volume":"43","author":"Xiao","year":"2012","journal-title":"Oceanol. Et Limnol. Sin."},{"key":"ref_6","first-page":"89","article-title":"Analysis of growth and development rules and growth curve fitting of Litopenaeus vannamei","volume":"11","author":"Li","year":"2015","journal-title":"South China Fish. Sci."},{"key":"ref_7","first-page":"99","article-title":"Growth performance and growth model of cage\u2014Reared lipfish bones","volume":"35","author":"Li","year":"2015","journal-title":"J. Guangdong Ocean Univ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/S0044-8486(99)00274-4","article-title":"Effects of water temperature and dissolved oxygen on daily feed consumption, feed utilization and growth of channel catfish (Ictalurus punctatus)","volume":"182","author":"Buentello","year":"2000","journal-title":"Aquaculture"},{"key":"ref_9","unstructured":"Qiangze, W. (2016). A Study on Intelligent Feeding System for Pond Culture, Nanjing University Agricultural."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.aquaeng.2015.02.001","article-title":"Development of an adaptive neural-based fuzzy inference system for feeding decision-making assessment in silver perch (Bidyanus bidyanus) culture","volume":"66","author":"Wu","year":"2015","journal-title":"Aquac. Eng."},{"key":"ref_11","first-page":"261","article-title":"Feed intake prediction model for group fish using the MEA-BP neuralnetwork in intensive aquaculture","volume":"7","author":"Chen","year":"2020","journal-title":"Inf. Process. Agric."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1080\/23328940.2020.1765950","article-title":"Effects of temperature on feeding and digestive processes in fish","volume":"7","author":"Volkoff","year":"2020","journal-title":"Temperature"},{"key":"ref_13","first-page":"5998","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Adv. Neural Inform. Process. Syst."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"109874","DOI":"10.1016\/j.compag.2024.109874","article-title":"Semi-supervised fish school density estimation and counting network in recirculating aquaculture systems based on adaptive density proxy","volume":"230","author":"Zhu","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"5189","DOI":"10.1007\/s00371-024-03715-6","article-title":"An enhanced underwater fish segmentation method in complex scenes using Swin transformer with cross-scale feature fusion","volume":"41","author":"Liu","year":"2024","journal-title":"Vis. Comput."},{"key":"ref_16","unstructured":"Liu, S., Yu, H., Liao, C., Li, J., Lin, W., Liu, A.X., and Dustdar, S. (2022, January 25\u201329). Pyraformer: Lowcomplexity pyramidal attention for long-range time series modeling and forecasting. Proceedings of the Tenth International Conference on Learning Representations, Virtual."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Zhang, R., and Hao, Y. (2024). Time Series Prediction Based on Multi-Scale Feature Extraction. Mathematics, 12.","DOI":"10.3390\/math12070973"},{"key":"ref_18","first-page":"42","article-title":"Sea bass culture technology i healthy pond culture technology of sea bass","volume":"8","author":"Lin","year":"2005","journal-title":"China Fish."},{"key":"ref_19","first-page":"29","article-title":"Attentional Feature Fusion","volume":"9","author":"Dai","year":"2020","journal-title":"Comput. Vis. Pattern Recognit."}],"container-title":["Journal of Sensor and Actuator Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2224-2708\/14\/4\/77\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:13:47Z","timestamp":1760033627000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2224-2708\/14\/4\/77"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,22]]},"references-count":19,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2025,8]]}},"alternative-id":["jsan14040077"],"URL":"https:\/\/doi.org\/10.3390\/jsan14040077","relation":{},"ISSN":["2224-2708"],"issn-type":[{"type":"electronic","value":"2224-2708"}],"subject":[],"published":{"date-parts":[[2025,7,22]]}}}