Parameters Influencing the Optimization Process in Airborne Particles PM10 Using a Neuro-Fuzzy Algorithm Optimized with Bacteria Foraging (BFOA)

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ISSN Print: 2163-0283
ISSN Online: 2163-0356
www.scirp.org/journal/ijis
E-mail: ijis@scirp.org

"Parameters Influencing the Optimization Process in Airborne Particles PM10 Using a Neuro-Fuzzy Algorithm Optimized with Bacteria Foraging (BFOA)"
written by Maria del Carmen Cabrera-Hernandez, Marco Antonio Aceves-Fernandez, Juan Manuel Ramos-Arreguin, Jose Emilio Vargas-Soto, Efren Gorrostieta-Hurtado,
published by International Journal of Intelligence Science, Vol.9 No.3, 2019

has been cited by the following article(s):

[1]	Performance evaluation of a recurrent deep neural network optimized by swarm intelligent techniques to model particulate matter
	Monge, MA Aceves-Fernández… - Journal of the Air & …, 2022

[2]	Airborne Particulate Matter Modeling: A Comparison of Three Methods Using a Topology Performance Approach
	Montañez, MA Aceves-Fernández… - Applied Sciences, 2021

[3]	Airborne particle pollution predictive model using Gated Recurrent Unit (GRU) deep neural networks
	2020

[1]	Research on Artificial Intelligence Machine Translation Based on Fuzzy Algorithm 2023 International Conference on Integrated Intelligence and Communication Systems (ICIICS), 2023 DOI:10.1109/ICIICS59993.2023.10421515

[2]	Airborne Particulate Matter Modeling: A Comparison of Three Methods Using a Topology Performance Approach Applied Sciences, 2021 DOI:10.3390/app12010256

[3]	Airborne particle pollution predictive model using Gated Recurrent Unit (GRU) deep neural networks Earth Science Informatics, 2020 DOI:10.1007/s12145-020-00462-9

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