کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5081516 | 1477604 | 2010 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A hybrid intelligent model for medium-term sales forecasting in fashion retail supply chains using extreme learning machine and harmony search algorithm
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
A hybrid intelligent (HI) model, comprising a data preprocessing component and a HI forecaster, is developed to tackle the medium-term fashion sales forecasting problem. The HI forecaster firstly adopts a novel learning algorithm-based neural network to generate initial sales forecasts and then uses a heuristic fine-tuning process to obtain more accurate forecasts based on the initial ones. The learning algorithm integrates an improved harmony search algorithm and an extreme learning machine to improve the network generalization performance. Extensive experiments based on real fashion retail data and public benchmark datasets were conducted to evaluate the performance of the proposed model. The experimental results demonstrate that the performance of the proposed model is much superior to traditional ARIMA models and two recently developed neural network models for fashion sales forecasting.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Production Economics - Volume 128, Issue 2, December 2010, Pages 614-624
Journal: International Journal of Production Economics - Volume 128, Issue 2, December 2010, Pages 614-624
نویسندگان
W.K. Wong, Z.X. Guo,