Análise hidrológica utilizando redes neurais para previsão de séries de vazões
YONEDA, S. L. (2014). Hydrologic analysis using Artificial Neural Networks for time series forecasting streamflow. (Master Degree) -Escola de Engenharia de São Carlos, Universidade de São Paulo, São Paulo, 2014. The inventory study aims to estimate the hydropower potential of rivers or basins , analyzing several alternative proposals for partition of falls , each of which contains a set of alternative hydroelectric developments . These alternatives are then individually analyzed to define the
... zed to define the optimal alternative, namely that which has the best cost benefit while causing less environmental damage. For this analysis we need to calculate the power of each specific use, as well as the energy generated for that then we need to know the flow of the river under study , the location of these usages. As the river flow varies with time because it depends on variables such as climate , geology, soils , deforestation , among others , we recommend using the long series of calculations mean flow at least 30 years of data , the problem is that in many cases we do not have these series or have smaller and incomplete series , in this case then we need to estimate the missing values and noisy data using next gauged stations , and then transport them to use in the study , for this we use statistical correlation techniques . The idea is that we use work instead of the conventional Artificial Neural Network techniques and compare the results.