January 2009

Computer Technology/Piping

Genetic algorithm tuning improves artificial neural network models

The technique is illustrated by predicting hold-up of slurry flow in pipelines

Ghanta, K. C., Lahiri, S. K., National Institute of Technology

A robust hybrid artificial neural network (ANN) methodology can offer superior performance for important process engineering problems. The method incorporates a hybrid artificial neural network and genetic algorithm technique (ANN-GA) for efficient tuning of ANN meta-parameters. The algorithm has been applied to predicting hold-up of solid–liquid slurry flow. A comparison with selected correlations in the literature showed that the developed ANN correlation noticeably improved hold-up prediction over a wide range of operating conditions, physical properties and pipe diameters. Introduction. In the past decade, artificial neural networks (ANNs) have emerged as attractive tools for

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