An Empirical Model of a Multiphase Reactor Based on Artificial Neural Network
نویسندگان
چکیده
An empirical model of a multiphase reactor based on artificial neural network has been developed. The multilayer feedforward network with one hidden layer has been used. The effect of the number of neurons in the hidden layer on the process parameters has also been examined. The model determines the system response to changes in the inlet variables. An optimum network architecture possessing good generalization ability has been determined in this study. The reactor model obtained from the network training process can be used in industrial practice for controlling the reactor in real time.
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