|No.15,North Third Loop East Road, Chaoyang District, Beijing, P.R.China|
School of Economics and Management Beijing, China
Beijing University of Chemical Technology
RePEc:edi:sebuccn (more details at EDIRC)
Research outputJump to: Articles
- Gang Kou & Lean Yu, 2015. "Intelligent knowledge management in operations research," Annals of Operations Research, Springer, vol. 234(1), pages 1-2, November.
- He, Kaijian & Yu, Lean & Tang, Ling, 2015. "Electricity price forecasting with a BED (Bivariate EMD Denoising) methodology," Energy, Elsevier, vol. 91(C), pages 601-609.
- Yu, Lean & Li, Jingjing & Tang, Ling & Wang, Shuai, 2015. "Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach," Energy Economics, Elsevier, vol. 51(C), pages 300-311.
- Tang, Ling & Wu, Jiaqian & Yu, Lean & Bao, Qin, 2015. "Carbon emissions trading scheme exploration in China: A multi-agent-based model," Energy Policy, Elsevier, vol. 81(C), pages 152-169.
- Yu, Lean & Wang, Zishu & Tang, Ling, 2015. "A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting," Applied Energy, Elsevier, vol. 156(C), pages 251-267.
- Lean Yu & Jingjing Li & Ling Tang, 2015. "Dynamic volatility spillover effect analysis between carbon market and crude oil market: a DCC-ICSS approach," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 38(4/5/6), pages 242-256.
- Pan, Wei & Yu, Lean & Wang, Shouyang & Wang, Xianjia, 2014. "A fuzzy multi-objective model for provider selection in data communication services with different QoS levels," International Journal of Production Economics, Elsevier, vol. 147(PC), pages 689-696.
- Yu, Lean & Zhao, Yang & Tang, Ling, 2014. "A compressed sensing based AI learning paradigm for crude oil price forecasting," Energy Economics, Elsevier, vol. 46(C), pages 236-245.
- Tang, Ling & Yu, Lean & He, Kaijian, 2014. "A novel data-characteristic-driven modeling methodology for nuclear energy consumption forecasting," Applied Energy, Elsevier, vol. 128(C), pages 1-14.
- Chen, Rongda & Yu, Lean, 2013. "A novel nonlinear value-at-risk method for modeling risk of option portfolio with multivariate mixture of normal distributions," Economic Modelling, Elsevier, vol. 35(C), pages 796-804.
- Lean Yu & Shouyang Wang & Fenghua Wen & Kin Lai, 2012. "Genetic algorithm-based multi-criteria project portfolio selection," Annals of Operations Research, Springer, vol. 197(1), pages 71-86, August.
- He, Kaijian & Yu, Lean & Lai, Kin Keung, 2012. "Crude oil price analysis and forecasting using wavelet decomposed ensemble model," Energy, Elsevier, vol. 46(1), pages 564-574.
- Tang, Ling & Yu, Lean & Wang, Shuai & Li, Jianping & Wang, Shouyang, 2012. "A novel hybrid ensemble learning paradigm for nuclear energy consumption forecasting," Applied Energy, Elsevier, vol. 93(C), pages 432-443.
- Wang, Shuai & Yu, Lean & Tang, Ling & Wang, Shouyang, 2011. "A novel seasonal decomposition based least squares support vector regression ensemble learning approach for hydropower consumption forecasting in China," Energy, Elsevier, vol. 36(11), pages 6542-6554.
- Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2009. "An intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: The case of credit scoring," European Journal of Operational Research, Elsevier, vol. 195(3), pages 942-959, June.
- Zhang, Xun & Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2009. "Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method," Energy Economics, Elsevier, vol. 31(5), pages 768-778, September.
- Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2008. "Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm," Energy Economics, Elsevier, vol. 30(5), pages 2623-2635, September.
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