The perception feed forward ANN isdesigned for the testing and training of data.

Having completed the performanceof experiment with 1% Pd doped SnO2 based thick film gas sensor thesensitivity shown by the sensor was found out to be maximum as 94.55% at 300°C . The maximum sensitivityrecorded for 1% Pd doping SnO2 based thick film gas sensor was94.55% at 300°C .

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Gradient Descent Backpropagation with adaptive learning ratenetwork function, the maximum sensitivity for tansin network transfer functionwas found to be 94.55% (300 ml concentration) at 300°C compare to othertransfer network function in. The Gradient Descent Backpropagation withadaptive learning rate network function was found to having minimum error intansin transfer function network. The multilayer perceptron feed forward ANNwas design for the testing and training purpose using Levenberg -Marquardt feedforward propagation. LEARNGDM is used as its adaptation learning function andMSE is used as performance function.

Tansin, Logsin and Purelin were used astransfer function for all the neurons respectively one by one each set of inputand output data. The Gradient Descent Backpropagation with adaptive learningrate network function was found to having minimum error in tansin transferfunction network. The performance of 1% Pd doped SnO2 based thickfilm gas sensor was best predicted by artificial neural network..

The maximumsensitivity recorded for 1% Pd doping sensor was calculated as 94.55% at 300°C.Levenberg-Marquardt feed forward propagation algorithm, the maximum sensitivity intansin network transfer function was found to be 94.54% at 300°C compare tonetwork other transfer function. Themaximum sensitivity recorded for 1% Pd doping sensor was 94.55% at 300°C. Whenthe sensitivity was tested by matlab software neural network tool through GradientDescent Backpropagation with adaptive learning rate algorithm network functionin purelin network transfer function, themaximum sensitivity for network was found to be 94.

54% at 300°C  as compared to Levenberg -Marquardtfeed forward propagation algorithm intansin network transfer function, the maximum sensitivity for network was foundas 94.55 % at 300 °C . Levenberg -Marquardt feed forward propagation algorithmis the most preferred technique in comparison to Gradient DescentBackpropagation with adaptive learning rate algorithm