Availability Prediction of the Repairable Equipment using Artificial Neural Network and Time Series Models

In this paper, one of the most important criterion in public services quality named availability is evaluated by using artificial neural network (ann). in addition, the availability values are predicted for future periods by using exponential weighted moving average (ewma) scheme and some time series models (tsm) including autoregressive (ar), moving average (ma) and autoregressive moving average (arma). results based on comparative studies between four methods based on ann and by considering the several conditions for the effective parameters in ann show that, the generalized regression method is the best method for predicting the availability. furthermore, results of the ewma and three mentioned tsm are also show the better performance of ma model for predicting the availability values in future periods.