Predicting Air Temperature and Relative Humidity Using a Statistical Inductive Learning Simulator

(Mansour bin Nasser new)

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Abstract

This paper present a Statistical Inductive Learning Simulator (SILS) to forecast the maximum daily temperature (maxdt) and the maximum daily relative humidity (maxrh) for the Saudi electrical company in Eastern Province. Predicting and visualizing engineering parameters is an essential issue for the electrical company to search for modern ways to cut losses due to the extreme consumption of electrical energy during summer season.
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