Memorias de investigación
Ponencias en congresos:
Supervised Metaplasticity for Big Data: Application to Pollutant Concentrations Forecast
Año:2017
Áreas de investigación
  • Ingenierías
Datos
Descripción
Artificial Metaplasticity Multilayer Perceptron is a training algorithm implementation for Artificial Neural Networks inspired in biological metaplasticity property of neurons and Shannon?s information theory. It is based on the hypothesis that a higher amount of informationfrom a Data Set is included in the most atypical data. Using this theory basis a supervised algorithm is developed giving more relevance to the less frequent patterns and subtracting relevance to the more frequent ones. This algorithm has achieved deeper learning on several mutidisciplinar data sets without the need of a Deep Network. The application of this algorithm to a key nowadays environmental problem: the pollutant concentrations prediction in cities, is now considered. The city selected is Salamanca, Mexico, that has been ranked as one of the most polluted cities in the world. The concerning registered pollutants are particles in the order of 10 ?m or less (PM10). The prediction of concentrations of those pollutants can be a powerful tool in order to take preventive measures such as the reduction of emissions and alerting the affected population. In this paper the results obtained are compared with previous recent published algorithms for the prediction of the pollutant concentration. Discussed and conclusions are presented.
Internacional
Si
Nombre congreso
IWINAC 2017 - International Work-conference on the Interplay between Natural and Artificial Computation
Tipo de participación
960
Lugar del congreso
La Coruña, Spain.
Revisores
Si
ISBN o ISSN
978-3-319-59772-0
DOI
10.1007/978-3-319-59773-7 38
Fecha inicio congreso
19/06/2017
Fecha fin congreso
23/06/2017
Desde la página
374
Hasta la página
383
Título de las actas
Biomedical Applications Based on Natural and Artificial Computing: International Work-Conference on the Interplay Between Natural and Artificial Computation, Proceedings, Part II.
Esta actividad pertenece a memorias de investigación
Participantes
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Automatización en Señal y Comunicaciones (GASC)
  • Departamento: Señales, Sistemas y Radiocomunicaciones