Conditioning of extreme learning machine for noisy data using heuristic optimization

This article provides a tool that can be used in the exact sciences to obtain good approximations to reality when noisy data is inevitable. Two heuristic optimization algorithms are implemented: Simulated Annealing and Particle Swarming for the determination of the extreme learning machine output we...

Full description

Autores:
Salazar, E
Mora, M
Vásquez, A
Gelvez, E
Tipo de recurso:
Fecha de publicación:
2020
Institución:
Universidad Simón Bolívar
Repositorio:
Repositorio Digital USB
Idioma:
eng
OAI Identifier:
oai:bonga.unisimon.edu.co:20.500.12442/6381
Acceso en línea:
https://hdl.handle.net/20.500.12442/6381
https://iopscience.iop.org/article/10.1088/1742-6596/1514/1/012007/pdf
Palabra clave:
Exact sciences
Data
Optimization algorithms
Heuristic algorithms
Rights
openAccess
License
Attribution-NonCommercial-NoDerivatives 4.0 Internacional