As artificial neural networks have been gaining importance in the field of engineering, this compilation aims to review the
scientific literature regarding the use of artificial neural networks for the modelling and optimization of food drying processes.
The applications of artificial neural networks in food engineering are presented, particularly focusing on control, monitoring
and modelling of industrial food processes. The authors emphasize the main achievements of artificial neural network modelling
in recent years in the field of quantitative structure -- activity relationships and quantitative structure -- retention relationships.
In the closing study, artificial intelligence techniques are applied to river water quality data and artificial intelligence
models are developed in an effort to contribute to the reduction of the cost of future on-line measurement stations.