6 research outputs found
Efficient Global Optimization using Deep Gaussian Processes
International audienceEfficient Global Optimization (EGO) is widely used for the optimization of computationally expensive black-box functions. It uses a surrogate modeling technique based on Gaussian Processes (Kriging). However, due to the use of a stationary covariance, Kriging is not well suited for approximating non stationary functions. This paper explores the integration of Deep Gaussian processes (DGP) in EGO framework to deal with the non-stationary issues and investigates the induced challenges and opportunities. Numerical experimentations are performed on analytical problems to highlight the different aspects of DGP and EGO
Evaluación de la estabilidad transitoria en sistemas eléctricos de potencia mediante redes de neuronas artificiales
Tesis (Doctor en Ing. Eléctrica) U.A.N.L.UANLhttp://www.uanl.mx