Using artificial neural network in demand prediction in Pichkooban company
Journal Title: Journal of Science and today’s world - Year 2015, Vol 4, Issue 7
Abstract
Prediction term base an its word meaning is imagination of a situation in future. Demand prediction is the most important issue about inventory management and for effective decision in inventory management, demand prediction for future periods are necessary. More over applying methods which results in increasing prediction precision were interested by management, economy and engineering fields. Neural networks were used as a powerful tool for predication in different fields in recent years. In this research demand prediction were considered by using neural networks. Neural network approach, multi-layered perceptron (MLP) with post-propagation learning were studied. Regarding to little information in network learning, adaptive calibration Algorithm were used. This technique has increased adaption capability of network and to some extent eliminated disadvantage of applied data loss. By using real data 1 production page type , Pichkooban company, prediction with real values compared and performance of real value methods in past period, past period mean, simple movable mean, balanced movable mean and profile smoothing with result of using.3-layer perceptron neural network were compared. In general, results show preference of MLP neural network model over other methods base on statistical performance criteria of MSE,MAD,MAPE.
Authors and Affiliations
Mohammad Mohammadi, Meisam Mohammadi
Keywords
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