Artificial neural network model with parameter tuning assisted by genetic algorithm technique: study of critical velocity of slurry flow in pipeline

作者：Lahiri S K^*; Ghanta K C

来源：Asia-Pacific Journal of Chemical Engineering, 2010, 5(5): 763-777.

DOI：10.1002/apj.403

• artificial neural network
• genetic algorithm
• slurry critical velocity
• slurry flow

This paper describes a robust hybrid artificial neural network (ANN) methodology, which can offer superior performance for important process engineering problems. The method incorporates hybrid artificial neural network and genetic algorithm technique (ANN-GA) for efficient tuning of ANN meta-parameters. The algorithm has been applied for prediction of critical velocity of solid liquid slurry flow. A comparison with selected correlations in the literature showed that the developed ANN correlation noticeably improved prediction of critical velocity over a wide range of operating conditions, physical properties, and pipe diameters.

• 出版日期2010-10