Authors :
Braide S
Volume/Issue :
Volume 7 - 2022, Issue 5 - May
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3yCdB6Z
DOI :
https://doi.org/10.5281/zenodo.6827659
Abstract :
The concept of Artificial Neural networks was
of McClloch and Pitts in 1943 and since then it has been
studied in details by scientists and engineers alike. This is
a study of the use of artificial neural network in analysis
of selected chemical engineering unit operations. In this
paper several networks were developed and trained for
three different unit operations. This paper deals with the
training of neural networks to perform predictions of
several chemical unit operations.
The feedforward neural network was trained to
model the bubble point temperature and pressure of the
water ethanol-water vapor-liquid equilibrium system. It
was found that the neural network predicted values with
high accuracy. Focused time-delay neural network was
used to model and predict the change in concentration of
the batch saponification reaction of ethyl acetate. The
response of the network in one step in time ahead
predictions was quite accurate. The dynamics of a CSTR
with a cooling jacket was also modeled with the NARX
neural network. The NARX model developed gave multi
step on time predictions with enormous aplomb.
Keywords :
artificial neural network; feedforward; supervised learning; cstr; batch reactor; VLE; dynamic network.
The concept of Artificial Neural networks was
of McClloch and Pitts in 1943 and since then it has been
studied in details by scientists and engineers alike. This is
a study of the use of artificial neural network in analysis
of selected chemical engineering unit operations. In this
paper several networks were developed and trained for
three different unit operations. This paper deals with the
training of neural networks to perform predictions of
several chemical unit operations.
The feedforward neural network was trained to
model the bubble point temperature and pressure of the
water ethanol-water vapor-liquid equilibrium system. It
was found that the neural network predicted values with
high accuracy. Focused time-delay neural network was
used to model and predict the change in concentration of
the batch saponification reaction of ethyl acetate. The
response of the network in one step in time ahead
predictions was quite accurate. The dynamics of a CSTR
with a cooling jacket was also modeled with the NARX
neural network. The NARX model developed gave multi
step on time predictions with enormous aplomb.
Keywords :
artificial neural network; feedforward; supervised learning; cstr; batch reactor; VLE; dynamic network.
