Results of Fitted Neural Network Models on Malaysian Aggregate Dataset

Nor Azura Md Ghani, Saadi Bin Ahmad Kamaruddin, Ismail Musirin, Hishamuddin Hashim

Abstract


This result-based paper presents the best results of both fitted BPNN-NAR and BPNN-NARMA on MCCI Aggregate dataset with respect to different error measures.  This section discusses on the results in terms of the performance of the fitted forecasting models by each set of input lags and error lags used, the performance of the fitted forecasting models by the different hidden nodes used, the performance of the fitted forecasting models when combining both inputs and hidden nodes, the consistency of error measures used for the fitted forecasting models, as well as the overall best fitted forecasting models for Malaysian aggregate cost indices dataset.


Keywords


Aggregate,Backpropagation, Neural network, Ordinary Nonlinear Autoregressive (NAR), Ordinary Nonlinear Autoregressive Moving Average (NARMA)

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