Benchmarking Machine Learning Models for Predicting the Average Weight of Oncorhynchus Mykiss in High Andean Fish Farming

Uceda P.; Torrel M.; Chavez S.; Ruiz R.; Sanchez S. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2026) · DOI: 10.18687/laccei2026.1.1.2262

Resumen

The present research compares Machine Learning models to predict growth (average final weight) and support profitability decisions in a high Andean fish farm. Linear and Random Forest Regression were evaluated using a set of 500 weekly records, integrating historical data provided by the fish farm and synthetic data generated within validated physicochemical ranges. The results concluded with a high performance in the growth prediction (R2>0.98) and adequate performance in profitability (R2≈0.87). In addition, the profitability classifier achieved 0.93 accuracy, suggesting operational utility as an early warning.

Instituciones: Universidad Privada del Norte