Forecasting erratic demand of medicines in a public hospital: A comparison of artificial neural networks and ARIMA models
نویسنده
چکیده
Demand planning is the process that helps in making decisions about inventory, in order to anticipate future demands from historical data. In an inventory with hundreds of items, a significant amount of these is subject to erratic demand. For these products, accurate forecasts are essential. This research work aims to show a comparison of ARIMA models and artificial neural networks for forecasting the demand medicines with an erratic nature.
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