Intelligent inventory forecasting system / Fadzlinor Mustapa

Abstract

This project is about producing a prototype of forecasting system by using artificial neural methods that will forecast stock level in the inventory. More specifically the project forecast the stock level of rice in the inventory for a specific period of time. This project has three objectives to be achieves. First, this project will doing a study on the inventory management and gathers all knowledge regarding the inventory. Second, the project with gather all knowledge about artificial neural network method. Lastly, this project must achieve an objective of developing a prototype of intelligent forecasting system that can make a prediction of the rice's stock level in the inventory. This project is hopefully can be beneficial to others. The general finding for this project is that with Back propagation algorithm, the suitable learning rate for forecasting prototype is 0.1 with architecture 7-11-1 that is seven nodes employed in the input layer, eleven nodes in the hidden layer and lastly one node employed in the output layer.

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