Forecast flows in a section of the Bogotá River by Artificial Intelligent Systems
William Moscoso$^{1}$, Luis Mauricio Agudelo$^{1}$
$^{1}$Universidad de La Sabana, Unisabana. Chía Colombia
Schedule:Wed 21st@10:15, Room: A

This article presents a comparison between two types of intelligent models: Artificial Neural Networks - ANN and Adaptative Neuro-Fuzzy Interference System - ANFIS, for forecasting flows in a section of Bogotá (Colombia) river, looking for the most efficient. The simulation was performed in the Matlab computer software, with data collected by hydrological stations of the Corporación Autónoma Regional of Cundinamarca (CAR), from September 2009 to October 2013. The findings suggest that by using artificial intelligence models you can reach a successful outcome, with Correlation Coefficients above 90% (CC), Mean Absolute Percentage Error (MAPE) below 12%, Concordance Correlation Coefficient to 84%, six other statistical evaluating precision and accuracy, suggesting that forecasts will be labeled as good and could think of the use of these techniques in Colombia.


	author 		= {William Moscoso and Luis Mauricio Agudelo},
	title 		= {Forecast flows in a section of the Bogotá River by Artificial Intelligent Systems},
	booktitle 	= {2015 XLI Latin American Computing Conference (CLEI)},
	pages 		= {346--352},
	year 		= {2015},
	editor 		= {Hector Cancela and Alex Cuadros-Vargas and Ernesto Cuadros-Vargas},
	address 	= {Arequipa-Peru},
	month 		= {October},
	organization 	= {CLEI},
	publisher 	= {CLEI},
	url 		= {},
	isbn 		= {978-1-4673-9143-6},

Generated by Ernesto Cuadros-Vargas , Sociedad Peruana de Computación-Peru, Universidad Católica San Pablo, Arequipa-Perú