In this investigation we studied the different electro-chromic properties of W03 thin films that relates on artificial
neural network. When electro-chromic energy storage devices stores energy for the changes colour, this is useful
in buildings as well as automobiles. Tungsten oxide is also known as tungsten anhydride (WO3). This material is
a combination of oxygen and tungsten. It is oxidative agent. Tungsten oxide or tungsten trioxide is used for
development of many things which are used in daily life for e.g. energy storage, gas sensors, smart window,
photocatalysis etc. The research investigation studies the WO3 thin film for supercapacitor. The simulation
process carried out in MATLAB here researchers checks the results generated by neural network and then that
results are matches with experimental results. For finding optimized supercapacitor we have calculated the error
which found at different hidden neurons in artificial neural network. In the conclusion of this study confirms
that ANN is appropriate tool for modelling of WO3 thin film for supercapacitor.


S. V. Katkar
Department of Computer Science, Shivaji University, Kolhapur, India.

K. G. Kharade
Department of Computer Science, Shivaji University, Kolhapur, India.

S. K. Kharade
Department of Mathematics, Shivaji University, Kolhapur, India.

R. K. Kamat
Department of Electronics, Shivaji University, Kolhapur, India.

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