Predicting System for Flooded Areas Developed with MLP-Type Neural Network

Forecasting systems can help in the intervention process of events in order to prevent them from occurring. Most of the existing methods use time series for the development and performance of the forecasting system. The purpose of this study is to observe the obtained results through the use of artificial multilayer neural networks. This work verified the efficiency of the proposed method for limnological water quality variables collected from the Paraguay River, corroborating with other studies that are used this tool in an attempt to predict events.