Advanced Optimization of Artificial Neural Networks for a Syngas Power Plant Using Bio-Inspired Optimization Algorithms: : Comparison Between PSO, GA and a Novel Mosquito Inspired Optimization Algorithm

The integration of renewable energies sources into hybrid distributed generation systems presents significant challenges, particularly when predicting critical. Syngas power plants are often integrated into hybrid microgrids to produce electricity instead of fossil fuel-based backup generators. This...

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Bibliographic Details

Published in:	IEEE Conference on Technologies for Sustainability (SusTech) (Online) pp. 1 - 6
Main Authors:	Aguila-Leon, Jesus, Vargas-Salgado, Carlos, Vega-Gomez, Carlos, Lucero-Tenorio, Miriam
Format:	Conference Proceeding
Language:	English
Published:	IEEE 20.04.2025
Subjects:	Artificial Neural Network Optimization Artificial neural networks Biomass Electricity Genetic algorithms Hybrid power systems Mosquito Mating Swarm Optimization (MMSO) Optimization Particle swarm optimization Prediction algorithms Renewable Energies Renewable Energy Prediction Sustainable development Syngas Syngas power plant
ISSN:	2640-6810
Online Access:	Get full text
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