Ahmad, Arshad (1995) Process identification using artificial neural network. Proceedings of The Eleventh Symposium of Malaysia Chemical Engineers . C3-1.
Recent years has seen the emergence of a new paradigm in systemâ€™s identification known as Artificial Neural Network (ANN). ANN is a methodology inspired from the structure and mechanism of human brain. Similar to the human brain (albeit in simplistic scale), ANN has the learning capability that enables it to remember past information. ANN is also known to be proficient in approximating nonlinear function to arbitrary accuracy in a black-box manner. As such, if adequate training over a sufficiently rich data is provided, the network will be able to capture the information contained within the data and store the in the form of model which can be utilize to predict future characteristics. This paper describes the basic mechanism of ANN and its application in the identification of polymerization process. The results obtained highlights the proficiency of ANN models in predicting the reactor product concentration, thus recommending its application in other model-related process engineering tasks.
|Uncontrolled Keywords:||Artificial neural network, black-box, identification process, polymerization process, reactor product concentration|
|Subjects:||T Technology > T Technology (General)|
|Divisions:||Chemical and Natural Resources Engineering (Formerly known)|
|Deposited By:||Norhani Jusoh|
|Deposited On:||01 Jan 2008 10:34|
|Last Modified:||01 Jun 2010 03:20|
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