TY - JOUR
T1 - Redes Neuronales Artificiales (RNA) aplicadas en la prediccion de caudales para intervalos de tiempo horarios
AU - Veintimilla Reyes, Jaime Eduardo
AU - francisco Cisneros Espinosa, Felipe Eduardo
PY - 2014/1/1
Y1 - 2014/1/1
N2 - The application of mathematical models in the management of hydrographic basins has demanding information requirements and for the most part they have not been developed to be applied in mountain regions. For this reason it is necessary to look for and implement models that do not have these requirements and that allow establishing relationships between the input and output data in a hydrographic basin. Computer techniques of artificial intelligence allow to establish relations between the input and output data in a hydrographic basin. The project seeks to evaluate different models of Artificial Neural Networks (RNA) in order to select one and implement it, with this it is intended to obtain the possibility of manipulating each of the connections of the model of the neural network to seek a rapid convergence and minimization of the margin of error. Once the model is calibrated, it is intended to make the prediction of flows for time intervals of less than 24 hours.
AB - The application of mathematical models in the management of hydrographic basins has demanding information requirements and for the most part they have not been developed to be applied in mountain regions. For this reason it is necessary to look for and implement models that do not have these requirements and that allow establishing relationships between the input and output data in a hydrographic basin. Computer techniques of artificial intelligence allow to establish relations between the input and output data in a hydrographic basin. The project seeks to evaluate different models of Artificial Neural Networks (RNA) in order to select one and implement it, with this it is intended to obtain the possibility of manipulating each of the connections of the model of the neural network to seek a rapid convergence and minimization of the margin of error. Once the model is calibrated, it is intended to make the prediction of flows for time intervals of less than 24 hours.
KW - RNA; Predicción de caudales
KW - RNA; Predicción de caudales
UR - https://www.aidep.org/es/node/631
M3 - Artículo
SN - 1390-3659
JO - Revista Tecnológica ESPOL
JF - Revista Tecnológica ESPOL
ER -