Multi-time Scale Attention Network for WEEE reverse logistics return prediction

Jia Zhang, Min Gao, Liang Zhao, Jiaqi Hu, Jinyong Gao, Meiling Deng, Chao Wan, Linda Yang

Abstract: Highlights•Multi-time Scale Attention Network model is proposed for WEEE return prediction.•Data features at multi-time scales are explored in modeling temporal dependencies.•Smooth embedding based on data aggregation is introduced to deal with high noise.•Four kinds of time positions are used for high sensitivity to temporal dependency.•Extensive experiments on real-world datasets demonstrate the model’s superiority.