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...
- 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