Prediction on the Seasonal Behavior of Hydrogen Sulfide Using a Neural Network Model

Models to predict seasonal hydrogen sulfide (H(2)S) concentrations were constructed using neural networks. To this end, two types of generalized regression neural networks and radial basis function networks are considered and optimized. The input data for H(2)S were collected from August 2005 to Fal...

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Detalles Bibliográficos
Autores principales: Kim, Byungwhan, Lee, Joogong, Jang, Jungyoung, Han, Dongil, Kim, Ki-Hyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: TheScientificWorldJOURNAL 2011
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5720030/
https://www.ncbi.nlm.nih.gov/pubmed/21552763
http://dx.doi.org/10.1100/tsw.2011.95

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5720030/
https://www.ncbi.nlm.nih.gov/pubmed/21552763
http://dx.doi.org/10.1100/tsw.2011.95

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