Universiti Teknologi Malaysia Institutional Repository

Pore size determination of asymmetric membrane using neural network

Mohd. Yusof, Khairiyah and Idris, Ani and Lim, J. S. Pore size determination of asymmetric membrane using neural network. In: International Conference on Chemical & Bioprocess Engineering, 27-29 August 2003, Kota Kinabalu.

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Abstract

This study, investigates the possibility of applying artificial neural network (ANN) as an alternative method to estimate the pore size of the asymmetric hollow fiber membranes. ANN, a connectionist-based (black box) model, consists of layers of nodes with nonlinear basis functions and weighted connections that link the nodes. Using the nodes and weights, the inputs are mapped to the outputs after being trained with a set of training data. The input data needed for training the ANN model, the solute rejection and the permeation rate, are obtained from permeation experiments. Since the number of experimental data points needed for training the ANN model is limited, stacked neural network is utilized instead of the more common and simple feedforward ANN. With the development of this ANN model, the procedure to estimate membrane pore size was found to be easier and faster with a testing error of less than 2% compared to the experimental data.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:asymmetric membranes, stacked network, artificial neural network, pore sizes
Subjects:T Technology > TP Chemical technology
Divisions:Chemical and Natural Resources Engineering (Formerly known)
ID Code:1048
Deposited By: Ms Zalinda Shuratman
Deposited On:23 Feb 2007 08:59
Last Modified:04 Jul 2017 03:25

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