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.
Author(s)Details
S. V.
Katkar
Department
of Computer Science, Shivaji University, Kolhapur, India.
K.
G. Kharade
Department of Computer Science,
Shivaji University, Kolhapur, India.
Department of Mathematics, Shivaji University, Kolhapur, India.
R. K. Kamat
Department of Electronics, Shivaji University, Kolhapur, India.
View Book :- http://bp.bookpi.org/index.php/bpi/catalog/book/233
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