The adjuster position prediction in energy meter calibration system using fuzzy learning method

The calibration process of the electric energy meter can be improved by using a supervised learning neural network algorithm for computing and determining the exact position adjuster. In this paper we attempt to use a combination of a learning method with a fuzzy inference system to obtain a more intuitive tool as well as more skilful calibration. This method can be used to predict the position of the energy meter adjuster to fit in with the error of the energy meter under calibration.