Artificial neural network model to predict compression-permeability characteristics of solid-liquid systems
A statistical modeling tool called artificial neural network (ANN) is used in this work to predict the compression-permeability (C-P) characteristics of a solid-liquid system. Extensive cake properties database containing experimental data spanning various material types, particle size distribution,...
Main Authors: | Iwata, Masashi, Jami, Mohammed Saedi, Shiojiri, Susumu |
---|---|
Format: | Article |
Language: | English |
Published: |
The Filtration Society and the American Filtration & Separations Society
2007
|
Subjects: | |
Online Access: | http://irep.iium.edu.my/40934/ http://irep.iium.edu.my/40934/ http://irep.iium.edu.my/40934/3/Published.pdf |
Similar Items
-
Determination of permeability characteristics of
solid/liquid separation using simplex algorithm
by: Tanaka, Takanori, et al.
Published: (2013) -
Potential of artificial neural networks in the prediction of wastewater treatment plant performance
by: Jami, Mohammed Saedi, et al.
Published: (2011) -
Water quality modelling and artificial neural network
by: Jami, Mohammed Saedi, et al.
Published: (2012) -
Driving force for solid/liquid separation under electric field
by: Tanaka, Takanori, et al.
Published: (2014) -
Analysis of constant-current electro-osmotic dewatering of various solid–liquid systems by considering the creep deformation
by: Iwata, Masashi, et al.
Published: (2007)