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Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
ISBN: 978-0-7695-3507-4
pp: 666-670
This paper addresses the issue of sales forecasting using a new approach based on connectionist and subspace decomposition methods.A tool is designed to support company management in the process of determining expected sales figures. Neural networks trained with a back-propagation algorithm are used to predict the weekly sales of a video game. For this purpose, optimal topology is found and a time-sensitive neural network is implemented. We have considered the use of many influencing indicators and parameters as inputs. In order to assess the relevance of these parameters, we perform a pre-processing based on Principal Component Analysis.
Sales forecasting, Neural networks, Principal component analysis, Data mining, Video games
Julie Marcoux, Sid-Ahmed Selouani, "A Hybrid Subspace-Connectionist Data Mining Approach for Sales Forecasting in the Video Game Industry", Computer Science and Information Engineering, World Congress on, vol. 05, no. , pp. 666-670, 2009, doi:10.1109/CSIE.2009.1001
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