A comparative sales forecast study between supervised and unsupervised learning algorithm on restaurant / Azhar Tamby

• Main Author: Tamby, Azhar
• Format: Student Project
• Language: English
• Published: Faculty of Information Technology and Quantitative Sciences 2006
• Subjects: Marketing research. Marketing research companies. Sales forecasting; Neural networks (Computer science); Algorithms; Restaurants, cafeterias, tearooms, etc.
• Online Access: http://ir.uitm.edu.my/id/eprint/1386/1/PPb_AZHAR%20TAMBY%20CS%2006_5%201.pdf; http://ir.uitm.edu.my/id/eprint/1386/

In this research, there are two algorithm of neural network will be used. It is coming from supervised and unsupervised learning algorithm. The Kohonen Self Organizing Map represents the unsupervised and Backpropagation represent the supervised. There will be a comparative study between these two algorithms with restaurant sales forecast as a scope. Some restaurant activities will be the input for the architecture to make a sales forecast. Each of the algorithm will used all the similar value including the learning rate in this research in order to make the comparison.