Predicting Tilapia Productivity in Geothermal Ponds: A Genetic Algorithm Approach for Sustainable Aquaculture Practices

Sustainability, Journal Year: 2024, Volume and Issue: 16(21), P. 9276 - 9276

Published: Oct. 25, 2024

This study presents a case focused on sustainable farming practices, specifically the cultivation of tilapia (Mozambican and aureus species) in ponds with geothermal water. research aims to optimize hydrochemical regime experimental enhance growth metrics external characteristics breeders. The dataset encompasses parameters fish feeding base from where were cultivated. Genetic algorithms (GA) employed for hyperparameter optimization (HPO) deep neural networks (DNN) prediction productivity each pond under varying conditions, achieving an R2 score 0.94. GA-driven HPO process is robust method optimizing aquaculture practices by accurately predicting how different conditions feed bases influence tilapia. By determining these factors, model promotes improving breeding outcomes maximizing aquaculture. approach can also be applied other systems, enhancing efficiency sustainability across various species.

Language: Английский

Investigating the metabolism of four sulfonamides in grass carp via HPLC-MS for screening candidate materials of matrix reference material

Food Chemistry, Journal Year: 2024, Volume and Issue: 464, P. 141657 - 141657

Published: Oct. 15, 2024

Language: Английский