International Journal of Intelligence Science

Volume 9, Issue 3 (July 2019)

ISSN Print: 2163-0283   ISSN Online: 2163-0356

Google-based Impact Factor: 0.58  Citations  

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

HTML  XML Download Download as PDF (Size: 9761KB)  PP. 67-91  
DOI: 10.4236/ijis.2019.93005    492 Downloads   1,386 Views  Citations

ABSTRACT

The airborne pollutants monitoring is an overriding task for humanity given that poor quality of air is a matter of public health, causing issues mainly in the respiratory and cardiovascular systems, specifically the PM10 particle. In this contribution is generated a base model with an Adaptive Neuro Fuzzy Inference System (ANFIS) which is later optimized, using a swarm intelligence technique, named Bacteria Foraging Optimization Algorithm (BFOA). Several experiments were carried with BFOA parameters, tuning them to achieve the best configuration of said parameters that produce an optimized model, demonstrating that way, how the optimization process is influenced by choice of the parameters.

Share and Cite:

Cabrera-Hernandez, M. , Aceves-Fernandez, M. , Ramos-Arreguin, J. , Vargas-Soto, J. and Gorrostieta-Hurtado, E. (2019) Parameters Influencing the Optimization Process in Airborne Particles PM10 Using a Neuro-Fuzzy Algorithm Optimized with Bacteria Foraging (BFOA). International Journal of Intelligence Science, 9, 67-91. doi: 10.4236/ijis.2019.93005.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.