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Eliana Maria Gonzalez-Neira, Jairo R. Montoya-Torres and Jose-Fernando Jimenez
This paper proposes a hybridized simheuristic approach that couples a greedy randomized adaptive search procedure (GRASP), a Monte Carlo simulation, a Pareto archived evolution strategy (PAES), and an analytic hierarchy process (AHP), in order to solve a...
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Zhengmao Chen, Dongyue Guo and Yi Lin
In this work, a deep Gaussian process (DGP) based framework is proposed to improve the accuracy of predicting flight trajectory in air traffic research, which is further applied to implement a probabilistic conflict detection algorithm. The Gaussian dist...
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Yeuntae Yoo, Seungmin Jung, Sungwoo Kang, Sungyoon Song, Jaehyeong Lee, Changhee Han and Gilsoo Jang
Renewable generation in power systems has proved to be challenging for system operators owing to the increasing levels of penetration. The operation of power systems currently requires additional flexibility and reserves due to the intermittency and unpr...
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Rodrigo L. Rose, Tejas G. Puranik and Dimitri N. Mavris
The complexity of commercial aviation operations has grown substantially in recent years, together with a diversification of techniques for collecting and analyzing flight data. As a result, data-driven frameworks for enhancing flight safety have grown i...
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Philippe Blondeel, Pieterjan Robbe, Cédric Van hoorickx, Stijn François, Geert Lombaert and Stefan Vandewalle
Civil engineering applications are often characterized by a large uncertainty on the material parameters. Discretization of the underlying equations is typically done by means of the Galerkin Finite Element method. The uncertain material parameter can be...
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