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...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE Conference on Technologies for Sustainability (SusTech) (Online) S. 1 - 6
Hauptverfasser:	Aguila-Leon, Jesus, Vargas-Salgado, Carlos, Vega-Gomez, Carlos, Lucero-Tenorio, Miriam
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 20.04.2025
Schlagworte:	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-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!