The enhanced BPNN-NAR and BPNN-NARMA models for Malaysian aggregate cost indices with outlying data

Ahmad Kamaruddin, Saadi and Md Ghani, Nor Azura and Mohamed Ramli, Norazan (2015) The enhanced BPNN-NAR and BPNN-NARMA models for Malaysian aggregate cost indices with outlying data. In: 2015 IIEEE Conference on e-Learning, e- Management and e-Services (IC3e), 24th-26th August 2015, Melaka, Malaysia.

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Abstract

Neurocomputing have been adapted in time series forecasting arena, but the presence of outliers that usually occur in data time series may be harmful to the data network training. This is because the ability to automatically find out any patterns without prior assumptions and loss of generality. In theory, the most common training algorithm for Backpropagation algorithms leans on reducing ordinary least squares estimator (OLS) or more specifically, the mean squared error (MSE). However, this algorithm is not fully robust when outliers exist in training data, and it will lead to false forecast future value. Therefore, in this paper, we present a new algorithm that manipulate algorithms firefly on least median squares estimator (FFA-LMedS) for Backpropagation neural network nonlinear autoregressive (BPNN-NAR) and Backpropagation neural network nonlinear autoregressive moving (BPNN-NARMA) models to reduce the impact of outliers in time series data. The performances of the proposed enhanced models with comparison to the existing enhanced models using M-estimators, Iterative LMedS (ILMedS) and Particle Swarm Optimization on LMedS (PSO-LMedS) are done based on root mean squared error (RMSE) values which is the main highlight of this paper. In the meanwhile, the real-industrial monthly data of Malaysian Aggregate cost indices data set from January 1980 to December 2012 (base year 1980=100) with different degree of outliers problem is adapted in this research. At the end of this paper, it was found that the enhanced BPNN-NARMA models using Mestimators, ILMedS and FFA-LMedS performed very well with RMSE values almost zero errors. It is expected that the findings would assist the respected authorities involve in Malaysian construction projects to overcome cost overruns.

Item Type:	Conference or Workshop Item (Plenary Papers)
Additional Information:	7581/50812
Uncontrolled Keywords:	BPNN, NAR, NARMA, firefly algorithm, least median squares
Subjects:	T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology
Depositing User:	Mr. Saadi Ahmad Kamaruddin
Date Deposited:	31 Mar 2017 09:50
Last Modified:	31 Mar 2017 09:51
URI:	http://irep.iium.edu.my/id/eprint/50812

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