Supervised learning of intra-daily recourse strategies for generation management under uncertainties
暂无分享,去创建一个
Louis Wehenkel | Boris Defourny | Bertrand Cornelusse | Gerald Vignal | L. Wehenkel | B. Cornélusse | Boris Defourny | G. Vignal
[1] M. Carrion,et al. A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem , 2006, IEEE Transactions on Power Systems.
[2] Ali S. Hadi,et al. Finding Groups in Data: An Introduction to Chster Analysis , 1991 .
[3] B. Cornelusse,et al. Automatic learning for the classification of primary frequency control behaviour , 2007, 2007 IEEE Lausanne Power Tech.
[4] W. Römisch,et al. Stochastic unit commitment in hydro-thermal power production planning , 2005 .
[5] Leo Breiman,et al. Classification and Regression Trees , 1984 .
[6] Claude Lemaréchal,et al. A primal-proximal heuristic applied to the French Unit-commitment problem , 2005, Math. Program..
[7] Bernhard Schölkopf,et al. A tutorial on support vector regression , 2004, Stat. Comput..
[8] Pierre Geurts,et al. Exploiting tree-based variable importances to selectively identify relevant variables , 2008, FSDM.
[9] Pierre Geurts,et al. Contributions to decision tree induction: bias/variance tradeoff and time series classification , 2002 .
[10] Werner Römisch,et al. Stochastic Lagrangian Relaxation Applied to Power Scheduling in a Hydro-Thermal System under Uncertainty , 2000, Ann. Oper. Res..
[11] Pierre Geurts,et al. Extremely randomized trees , 2006, Machine Learning.
[12] P. Carpentier,et al. Stochastic optimization of unit commitment: a new decomposition framework , 1996 .