每年的科研成果
每年的科研成果
个人简介
与联合国可持续发展目标相关的专业知识
2015 年，联合国成员国同意 17 项可持续发展目标 (SDG)，以消除贫困、保护地球并确保全人类的繁荣。此人的工作有助于实现下列可持续发展目标：
指纹图谱
深入其中 Xi Xiang 为活跃的研究主题。这些主题标签来自此人的成果。它们共同形成唯一的指纹。
最近五年的合作关系和顶尖研究领域
最近的国家/地区级外部合作关系。点击圆点，以了解详细信息或
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Adaptive incentive mechanism with predictors for on-time attended home delivery problem
Xiang, X., Liu, C. & Gong, L., 11月 2024, 在: Computers and Industrial Engineering. 197, 110570.科研成果: 期刊稿件 › 文章 › 同行评审
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A GCN-based adaptive generative adversarial network model for short-term wind speed scenario prediction
Liu, X., Yu, J., Gong, L., Liu, M. & Xiang, X., 1 5月 2024, 在: Energy. 294, 130931.科研成果: 期刊稿件 › 文章 › 同行评审
5 引用 （Scopus） -
An Adaptive Dynamic Scheduling Policy for the Integrated Optimization Problem in Automated Transshipment Hubs
Xiang, X., Lee, L. H. & Chew, E. P., 2024, 在: IEEE Transactions on Automation Science and Engineering. 21, 3, 页码 2701-2715 15 页码科研成果: 期刊稿件 › 文章 › 同行评审
1 引用 （Scopus） -
A short-term wind power probability prediction method based on soft clustering and similarity measurement
Liu, Z., Liu, X., Gong, L., Liu, M., Xiang, X., Xie, J. & Zhang, Y., 2024, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control, METMS 2024. Khan, Z. H., Zhang, J. & Zeng, P. (编辑). SPIE, 131633P. (Proceedings of SPIE - The International Society for Optical Engineering; 卷 13163).科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审
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Deep graph temporal convolutional neural networks for short-term wind speed prediction
Yu, J., Liu, X., Gong, L., Liu, M., Xiang, X., Xie, J. & Zhang, Y., 2024, 2024 4th International Conference on Neural Networks, Information and Communication Engineering, NNICE 2024. Institute of Electrical and Electronics Engineers Inc., 页码 213-216 4 页码 (2024 4th International Conference on Neural Networks, Information and Communication Engineering, NNICE 2024).科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审