Helbert E. Espitia

According to our database1, Helbert E. Espitia authored at least 14 papers between 2011 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

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Bibliography

2019
Considerations for parameter configuration on Vortex Particle Swarm Optimization.
Theor. Comput. Sci., 2019

Proposal of an Adaptive Neurofuzzy System to Control Flow Power in Distributed Generation Systems.
Complexity, 2019

Control of a Microturbine Using Neural Networks.
Proceedings of the Applied Computer Sciences in Engineering, 2019

2018
Statistical analysis for vortex particle swarm optimization.
Appl. Soft Comput., 2018

Control of a Permanent Magnet Synchronous Generator Using a Neuro-Fuzzy System.
Proceedings of the Applied Computer Sciences in Engineering, 2018

Prototype of a Recommendation System Based on Multi-agents in the Analysis of Movies Dataset.
Proceedings of the Applied Computer Sciences in Engineering, 2018

2017
MOVPSO: Vortex Multi-Objective Particle Swarm Optimization.
Appl. Soft Comput., 2017

Analysis of Power Quality for Connections in the Same Circuit of Metal-Halide, LED and Compact Fluorescent Lamps.
Proceedings of the Applied Computer Sciences in Engineering, 2017

2016
Statistical analysis of a multi-objective optimization algorithm based on a model of particles with vorticity behavior.
Soft Comput., 2016

Comparison Between Neuronal Networks and ANFIS for Wind Speed-Energy Forecasting.
Proceedings of the Applied Computer Sciences in Engineering, 2016

Simulation of the Coffee Berry Borer Expansion in Colombian Crops Using a Model of Multiple Swarms.
Proceedings of the Applied Computer Sciences in Engineering, 2016

2013
Vortex Particle Swarm Optimization.
Proceedings of the IEEE Congress on Evolutionary Computation, 2013

2012
Fuzzy controller design using concretion based on boolean relations (CBR).
Proceedings of the 12th UK Workshop on Computational Intelligence, 2012

2011
Path planning of mobile robots using potential fields and swarms of Brownian particles.
Proceedings of the IEEE Congress on Evolutionary Computation, 2011


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