个人信息
参与实验室科研项目
人机智能协同关键技术及其在智能制造中的应用
非可信智能驱动的可靠智造
研究课题
基于多尺度特征提取的滚动轴承剩余使用寿命预测方法研究
学术成果
共撰写/参与撰写专利 0 项，录用/发表论文 1 篇，投出待录用论文0篇。
Conference Articles
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DC-Mamber: A Dual Channel Prediction Model Based on Mamba and Linear Transformer for Multivariate Time Series Forecasting
Bing Fan,
Shusen Ma,
Yun-Bo Zhao ,
and Gang Xu
In ICASSP 2026 - 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
2026
[Abs]
[doi]
[pdf]
Multivariate time series forecasting (MTSF) requires capturing both local intra-variable patterns and global crosstimestep dependencies. Existing data processing strategies are divided into channel-independent, focusing on each variable’s local temporal features, and channel-mixing, emphasizing global temporal dependencies. Mainstream models are based on Transformer and the emerging Mamba. Transformers effectively model global dependencies but face quadratic complexity and weak local sensitivity, while Mamba, based on state space models (SSMs), achieves linear complexity and efficient long-range modeling yet struggles with parallel global contextual information. To address these limitations, we propose DC-Mamber, a dual-channel prediction model based on Mamba and linear Transformer. Specifically, DCMamber employs a Dual-Channel Embedding Layer to map inputs into two streams reflecting distinct strategies, which are processed separately by a Dual-Channel Encoder and subsequently integrates the outputs via a Feature-fusion module. Experiments on four datasets demonstrate DC-Mamber’s superior accuracy over existing models.
博客文章
学位论文
毕业去向
中国科学技术大学， 博士研究生