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发布日期:2024-05-10 专利申请、商标注册、软件著作权、资质办理快速响应 微信:543646


李维
姓名 李维 性别 李维
学校 哈尔滨工业大学 部门 经济与管理学院
学位 李维 学历 李维
职称 副教授 联系方式 wei.li@hit.edu.cn
邮箱 wei.li@hit.edu.cn    
软件产品登记测试全国受理 软件著作权666元代写全部资料全国受理 实用新型专利1875代写全部资料全国受理
李维

基本信息 科学研究 新建主栏目 教育经历 名称 2018.08-2021.12: 挪威科技大学, 金融计算,博士 2016.09-2017.09: 伦敦玛丽女王大学,金融计算,硕士 2015.09-2016.09: 格拉斯哥大学,金融预测与投资,硕士 2007.09-2009.07: 吉林大学,工商管理,学士 2005.09-2009.07: 吉林大学,动物科学,学士 工作经历 名称 2024.03-至今: 哈尔滨工业大学,经济管理学院, 副教授 2022.02-2024.02: 新加坡国立大学,商业分析与运营学院, 博士后研究员 2021.02-2022.01: 柏林洪堡大学,经济商学院,访问学者 研究方向 名称 金融计算,可解释性机器学习,能源金融,供应链金融 期刊论文 名称 [1] Li, W.*, Paraschiv, F. (2021). Modelling the Evolution of Wind and Solar Power Infeed Fore- casts. Journal of Commodity Markets. DOI: https://doi.org/10.1016/j.jcomm.2021.100189. [2] Li, W.*, Becker, M. D. (2021). Day-ahead Electricity Price Prediction Applying Hybrid Models of LSTM-based Deep Learning Methods and Feature Selection Algorithms under Consideration of Market Coupling. Energy. DOI: https://doi.org/10.1016/j.energy.2021.121543. [3] 王茹婷,彭方平*,李维,王春丽 (2022). 打破刚性兑付能降低企业融资成本吗? 管理世界. DOI: https://doi.org/10.19744/ j.cnki.11-1235/f.2022.0051. [4] Li, W., Paraschiv, F., Sermpinis, G.* (2022). A Data-driven Explainable Case-based Reasoning for Financial Risk Detection. Quantitative Finance. DOI: https://doi.org/10.1080/14697688. 2022.2118071. [5] Sun, Q., Li, W., Meng, Q.* (2024). Single-leg shipping revenue management for expedited services with ambiguous elasticity in transit-time-sensitive demand. Transportation Research Part B: Methodological. DOI: https://doi.org/10.1016/j.trb.2024.10288. 1. Li, W.*, Paraschiv, F. (2021). Modelling the Evolution of Wind and Solar Power Infeed Fore-casts. Journal of Commodity Markets. DOI: https://doi.org/10.1016/j.jcomm.2021.100189.2. Li, W.*, Becker, M. D. (2021). Day-ahead Electricity Price Prediction Applying Hyb Li, W.*, Paraschiv, F. (2021). Modelling the Evolution of Wind and Solar Power Infeed Fore- casts. Journal of Commodity Markets. DOI: https://doi.org/10.1016/j.jcomm.2021.100189. 2. Li, W.*, Becker, M. D. (2021). Day-ahead Electricity Price Prediction Applying Hybrid Models of LSTM-based Deep Learning Methods and Feature Selection Algorithms under Consideration of Market Coupling. Energy. DOI: https://doi.org/10.1016/j.energy.2021.121543. 3. Wang, R.T., Peng, F.P.*, Li, W., Wang, C.L. (2022). Does Terminating Rigid Payment Diminish Financing Cost? Management World. (Language: Chinese). DOI: https://doi.org/10.19744/ j.cnki.11-1235/f.2022.0051. 4. Li, W., Paraschiv, F., Sermpinis, G.* (2022). A Data-driven Explainable Case-based Reasoning for Financial Risk Detection. Quantitative Finance. DOI: https://doi.org/10.1080/14697688. 2022.2118071.of LSTM-based Deep Learning Methods and Feature Selection Algorithms under Consideration ofMarket Coupling. Energy. DOI: https://doi.org/10.1016/j.energy.2021.121543. Modelsof LSTM-based Deep Learning Methods and Feature Selection Algorithms under Consideration ofMarket Coupling. Energy. DOI: https://doi.org/10.1016/j.energy.2021.121543.3. Wang, R.T., Peng, F.P.*, Li, W., Wang, C.L. (2022). Does Terminating Rigid Payment DiminishFinancing Cost? Management World. (Language: Chinese). DOI: https://doi.org/10.19744/j.cnki.11-1235/f.2022.0051.4. Li, W., Paraschiv, F., Sermpinis, G.* (2022). A Data-driven Explainable Case-based Reasoningfor Financial Risk Detection. Quantitative Finance. DOI: https://doi.org/10.1080/14697688.2022.2118071.