Zi Yang Adrian Ang

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Thermoelectric generators (TEG) convert the thermal energy flowing through them into electrical energy in a quantity dependent on the temperature gradient across the thermocouple between the TEG ceramic substrates. Electrical outputs generated by the TEG shown on technical sheets provided by the manufacturer are usually a mismatch to the actual energy(More)
This paper presents an integrated artificial neural network (ANN) approach for the design and prediction of energy generated from a thermoelectric generator (TEG) under the influence of the operating environmental parameters. The unique ANN model can predict the output voltage generated as well as ensuring the reliability of the output. Deriving of(More)
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