The perception feed forward ANN is
designed for the testing and training of data. Having completed the performance
of experiment with 1% Pd doped SnO2 based thick film gas sensor the
sensitivity shown by the sensor was found out to be maximum as 94.55% at 300°C . The maximum sensitivity
recorded for 1% Pd doping SnO2 based thick film gas sensor was
94.55% at 300°C .Gradient Descent Backpropagation with adaptive learning rate
network function, the maximum sensitivity for tansin network transfer function
was found to be 94.55% (300 ml concentration) at 300°C compare to other
transfer network function in. The Gradient Descent Backpropagation with
adaptive learning rate network function was found to having minimum error in
tansin transfer function network. The multilayer perceptron feed forward ANN
was design for the testing and training purpose using Levenberg -Marquardt feed
forward propagation. LEARNGDM is used as its adaptation learning function and
MSE is used as performance function. Tansin, Logsin and Purelin were used as
transfer function for all the neurons respectively one by one each set of input
and output data. The Gradient Descent Backpropagation with adaptive learning
rate network function was found to having minimum error in tansin transfer
function network. The performance of 1% Pd doped SnO2 based thick
film gas sensor was best predicted by artificial neural network..The maximum
sensitivity recorded for 1% Pd doping sensor was calculated as 94.55% at 300°C.Levenberg
-Marquardt feed forward propagation algorithm, the maximum sensitivity in
tansin network transfer function was found to be 94.54% at 300°C compare to
network other transfer function. The
maximum sensitivity recorded for 1% Pd doping sensor was 94.55% at 300°C. When
the sensitivity was tested by matlab software neural network tool through Gradient
Descent Backpropagation with adaptive learning rate algorithm network function
in purelin network transfer function, the
maximum sensitivity for network was found to be 94.54% at 300°C  as compared to Levenberg -Marquardt
feed forward propagation algorithm in
tansin network transfer function, the maximum sensitivity for network was found
as 94.55 % at 300 °C . Levenberg -Marquardt feed forward propagation algorithm
is the most preferred technique in comparison to Gradient Descent
Backpropagation with adaptive learning rate algorithm 

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