کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
385718 | 660872 | 2011 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Sales forecasting system based on Gray extreme learning machine with Taguchi method in retail industry Sales forecasting system based on Gray extreme learning machine with Taguchi method in retail industry](/preview/png/385718.png)
Due to the strong competition that exists today, most retailers are in a continuous effort for increasing profits and reducing their cost. An accurate sales forecasting system is an efficient way to achieve the aforementioned goals and lead to improve the customers’ satisfaction, reduce destruction of products, increase sales revenue and make production plan efficiently. In this study, the Gray extreme learning machine (GELM) integrates Gray relation analysis and extreme learning machine with Taguchi method to support purchasing decisions. GRA can sieve out the more influential factors from raw data and transforms them as the input data in a novel neural network such as ELM. The proposed system evaluated the real sales data in the retail industry. The experimental results demonstrate that our proposed system outperform several sales forecasting methods which are based on back-propagation neural networks such as BPN and MFLN models.
Journal: Expert Systems with Applications - Volume 38, Issue 3, March 2011, Pages 1336–1345