Evaluation of a Recurrent Neural Network LSTM for the Detection of Exceedances of Particles PM10. - Julio Alberto Ramírez Montañez; Marco Antonio Aceves-Fernández; Saúl Tovar-Arriaga; Juan Manuel Ramos-Arreguín; Giovanni Angelo Salini Calderon (CCE, 2019)

Propuesta de mejora de modelado de partículas contaminantes PM10 mediante algoritmos de inteligencia colectiva de bacteria BFOA. - María del Cármen Cabrera-Hernández; Julio Alberto Ramírez Montañez; Marco Antonio Aceves-Fernández; Jesús Carlos Pedraza-Ortega; Juan Manuel Ramos-Arreguín (Res. Comput. Sci., 2019)

Capability of a Recurrent Deep Neural Network Optimized by Swarm Intelligence Techniques to Predict Exceedances of Airborne Pollution (PMx) in Largely Populated Areas. - Gerardo Javier Kuri-Monge; Marco Antonio Aceves-Fernández; Julio Alberto Ramírez Montañez; Jesús Carlos Pedraza-Ortega (ICIT, 2021)

Capability of an Elman Recurrent Neural Network for predicting the non-linear behavior of airborne pollutants. - David Barrero-González; Julio Alberto Ramírez Montañez; Marco Antonio Aceves-Fernández; Juan Manuel Ramos-Arreguín (Earth Sci. Informatics, 2022)