Modelo para la predicción del consumo de agua potable mediante redes neuronales artificiales en la ciudad de Iquitos

• Autores: Carranza Serrantes, Fernando Jan Pierre, Vargas Lozano, Franco Xavier
• Formato: tesis de maestría
• Fecha de Publicación: 2023
• Institución: Universidad Nacional De La Amazonía Peruana
• Repositorio: UNAPIquitos-Institucional
• Lenguaje: español
• OAI Identifier: oai:repositorio.unapiquitos.edu.pe:20.500.12737/9334
• Enlace del recurso: https://hdl.handle.net/20.500.12737/9334
• Nivel de acceso: acceso abierto
• Materia: Ingeniería dirigida por modelos; Modelo de simulación; Redes neuronales; Redes de distribución de agua; Desarrollo de software de aplicación; https://purl.org/pe-repo/ocde/ford#2.02.04

The research work addresses the problem of water supply management in the city of Iquitos, where the question arises: Can an Artificial Neural Network model based on relevant historical data improve the prediction of the distributed volume of drinking water in the City of Iquitos?, to answer this question, the general objective of implementing an Artificial Neural Network model based on relevant historical data and evaluating its ability to accurately predict the distributed volume of drinking water in the City of Iquitos was raised. The methodology used was of the applied type, with a quantitative approach, the sample corresponded to the historical data of distributed volume of drinking water during the last six years. The results showed that the Artificial Neural Network model was able to accurately predict the distributed volume of drinking water in the city, identifying the maximum temperature, the minimum temperature, and the population as significant variables for the prediction of drinking water consumption. The implementation of this model can be useful for the management of water supply in the city and for future research in the field.