Application of GMDH-type Neural Network for Pathloss Predictions,

Abstract

This paper proposes the use of Group Method of Data Handling (GMDH) technique for Path Loss Prediction as a non-linear function approximation in Cellular mobile network propagation losses. The paper compared prediction accuracy of GMDH with adaptive neuro-fuzzy inference systems (ANFIS) using four statistical performance indices with actual signal strength measurement taken at certain suburban areas of Bauchi metropolis, Nigeria. The proposed GMDH model was found to offer improved prediction results in terms of reducing the root mean square error (RMSE) and mean absolute error by 33.26% and 21.86% respectively over the ANFIS model.