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Fashion Color Forecasting by Applying an Improved Back Propagation Neural Network 被引量:2
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作者 常丽霞 潘如如 高卫东 《Journal of Donghua University(English Edition)》 EI CAS 2013年第1期58-62,共5页
Fashion color forecasting is one of the most important factors for fashion marketing and manufacturing. Several models have been applied by previous researchers to conduct fashion color forecasting. However, few convi... Fashion color forecasting is one of the most important factors for fashion marketing and manufacturing. Several models have been applied by previous researchers to conduct fashion color forecasting. However, few convincing forecasting systems have been established. A prediction model for fashion color forecasting was established by applying an improved back propagation neural network (BPNN) model in this paper. Successive six-year fashion color palettes, released by INTERCOLOR, were used as learning information for the neural network to develop a reliable prediction model. Colors in the palettes were quantified by PANTONE color system. Additionally, performance of the established model was compared with other GM(1, 1) models. Results show that the improved BPNN model is suitable to predict future fashion color trend. 展开更多
关键词 fashion color back propagation neural network(BPNN) trend forecasting momentum factor
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