Predictive Modeling of Water Level in the San Juan River Using Hybrid Neural Networks Integrated with Kalman Smoothing Methods

Predictive Modeling of Water Level in the San Juan River Using Hybrid Neural Networks Integrated with Kalman Smoothing Methods

This study presents an innovative approach to predicting the water level in the San Juan River, Chocó, Colombia, by implementing two hybrid models: nonlinear auto-regressive with exogenous inputs (NARX) and long short-term memory (LSTM). These models combine artificial neural networks with smoothing...

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Bibliographic Details
Main Authors: Jackson B. Renteria-Mena, Eduardo Giraldo
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Information
Subjects:
filtering techniques
hydrological forecasting
time series models
nonlinear models
parameter estimation
Online Access:https://www.mdpi.com/2078-2489/15/12/754
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