A mathematical model to predict particleboard properties using the GMDH-type neural network and genetic algorithm
Abstract In this study, GMDH neural network based on genetic algorithm was used to predict the physical and mechanical properties of laboratory made particleboard. To predict the mechanical and physical properties of particleboard we used input parameters such as neural network including press clos...
Guardado en:
Autores principales: | Zahra Jahanilomer, Saeed Reza farrokhpayam, Mohammad Shamsian |
---|---|
Formato: | article |
Lenguaje: | FA |
Publicado: |
Regional Information Center for Science and Technology (RICeST)
2014
|
Materias: | |
Acceso en línea: | https://doaj.org/article/eeb2d32a64cc4842afc09778291d3542 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
An Intelligent Neural Networks System for Prediction of particleboard properties
por: Zahra Jahani lomer, et al.
Publicado: (2014) -
The effect of wood species on particleboard properties
por: masoudreza habibi, et al.
Publicado: (2010) -
The Potential of Utilization of Cotton Stalk Residues In Particleboard Production
por: Abolfazl Kargarfard
Publicado: (2017) -
The Effects of Acetylated Poplar Particles on Applicational Properties of manufactured Particleboards with Isocyanate Resin
por: Hamideh Abdolzadeh, et al.
Publicado: (2009) -
Investigation of the sound absorption properties of gypsum particleboard
produced with kenaf stalks and nano clay
por: Hossein Rangavar, et al.
Publicado: (2014)