<![CDATA[Grounding is crucial to achieving equipment and personnel protection. This paper presents input-output pair-based modeling using the response surface method and artificial neural network to predict earth resistance for novel factors associated with grounding. The effect of various types of cone-shaped earth electrodes, charcoal size, and industrial waste metal fibers on earth resistance is investigated for the first time. The experimental trials are carried out in a scaled down manner. Artificial neural network and response surface method are used as investigatory tool for parametric variation. Artificial neural network model predicts earth resistance with more accuracy as compared to response surface method. These methods are found to be very effective in prediction of earth resistance of grounding system which is complex in nature.]]>
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