Memorias de investigación
Communications at congresses:
Supervised Metaplasticity for Big Data: Application to Pollutant Concentrations Forecast
Year:2017
Research Areas
  • Engineering
Information
Abstract
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.
International
Si
Congress
IWINAC 2017 - International Work-conference on the Interplay between Natural and Artificial Computation
960
Place
La Coruña, Spain.
Reviewers
Si
ISBN/ISSN
978-3-319-59772-0
10.1007/978-3-319-59773-7 38
Start Date
19/06/2017
End Date
23/06/2017
From page
374
To page
383
Biomedical Applications Based on Natural and Artificial Computing: International Work-Conference on the Interplay Between Natural and Artificial Computation, Proceedings, Part II.
Participants
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Automatización en Señal y Comunicaciones (GASC)
  • Departamento: Señales, Sistemas y Radiocomunicaciones