Predicción de oxígeno disuelto en acuacultura semi-intensiva con redes neuronales artificiales

Currently, farming of aquatic species for human consumption is a worldwide practice performed. Hence, dissolved oxygen is one of the most important parameters of water quality in aquaculture systems, so maintaining good levels of concentration of this gas is essential for a successful production. This work presents a predictive model based on Artificial Neural Networks (ANNs), which are designed with the FS-EPNet evolutionary algorithm to estimate water quality based on the amount of dissolved oxygen in white shrimp farming. The results show a good performance by the evolved RNAs, so