ARTIFICIAL NEURAL NETWORK BASED DEMAND FORECASTING INTEGRATED WITH FEDERAL FUNDS RATE
Anupa ARACHCHIGE
anupa13@hotmail.comUniversity of Moratuwa, Faculty of Engineering, Department of Transport and Logistics, Moratuwa (Sri Lanka)
Ranil SUGATHADASA
University of Moratuwa, Faculty of Engineering, Department of Transport and Logistics, Moratuwa (Sri Lanka)
Oshadhi HERATH
University of Moratuwa, Faculty of Engineering, Department of Transport and Logistics, Moratuwa (Sri Lanka)
Amila THIBBOTUWAWA
University of Moratuwa, Faculty of Engineering, Department of Transport and Logistics, Moratuwa (Sri Lanka)
Abstract
Adverse effects of inaccurate demand forecasts; stockouts, overstocks, customer loss have led academia and the business world towards accurate demand forecasting methods. Artificial Neural Network (ANN) is capable of highly accurate forecasts integrated with many variables. The use of Price and Promotion variables have increased the accuracy while the addition of other relevant variables would decrease the occurrences of errors. The use of the Federal Funds Rate as an additional macroeconomic variable to ANN forecasting models has been discussed in this research by the means of the accuracy measuring method: Average Relative Mean Absolute Error.
Keywords:
demand forecasting, artificial neural network, price, promotion, federal funds rateReferences
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Authors
Anupa ARACHCHIGEanupa13@hotmail.com
University of Moratuwa, Faculty of Engineering, Department of Transport and Logistics, Moratuwa Sri Lanka
Authors
Ranil SUGATHADASAUniversity of Moratuwa, Faculty of Engineering, Department of Transport and Logistics, Moratuwa Sri Lanka
Authors
Oshadhi HERATHUniversity of Moratuwa, Faculty of Engineering, Department of Transport and Logistics, Moratuwa Sri Lanka
Authors
Amila THIBBOTUWAWAUniversity of Moratuwa, Faculty of Engineering, Department of Transport and Logistics, Moratuwa Sri Lanka
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