Intelligent inventory forecasting system / Fadzlinor Mustapa

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.