A General Regression Neural Network model for construction equipment maintenance costs

This paper presents a time series analysis based on General Regression Neural Networks (GRNN) models to address the prediction of construction equipment maintenance costs. The results show that GRNN can model the behaviour and predict the maintenance costs for different equipment categories and fleet with satisfactory accuracy. The paper also discusses the effects of incorporation of the parallel fuel consumption data as explanatory time series to modelling performance.