Zobrazeno 1 - 10
of 616
pro vyhledávání: '"EVERSON, RICHARD"'
Trajectory prediction (TP) plays an important role in supporting the decision-making of Air Traffic Controllers (ATCOs). Traditional TP methods are deterministic and physics-based, with parameters that are calibrated using aircraft surveillance data
Externí odkaz:
http://arxiv.org/abs/2309.14957
Autor:
Pepper, Nick, Thomas, Marc, De Ath, George, Oliver, Enrico, Cannon, Richard, Everson, Richard, Dodwell, Tim
Ensuring vertical separation is a key means of maintaining safe separation between aircraft in congested airspace. Aircraft trajectories are modelled in the presence of significant epistemic uncertainty, leading to discrepancies between observed traj
Externí odkaz:
http://arxiv.org/abs/2210.01445
Autor:
Lee, Bina, Choi, Ha Nyeoung, Che, Young Hyun, Ko, Myungjun, Seong, Hye Min, Jo, Min Gi, Kim, Seon-Hee, Song, Chieun, Yoon, Subeen, Choi, Jiwoo, Kim, Jeong Hee, Kim, Minkyeong, Lee, Min Young, Park, Sang Won, Kim, Hye Jung, Kim, Seong Jae, Moon, Do Sik, Lee, Sun, Park, Jae-Hoon, Yeo, Seung-Geun, Everson, Richard G., Kim, Young Jin, Hong, Kyung-Wook, Roh, In-Soon, Lyoo, Kwang-Soo, Kim, Yong Jun, Yun, Seung Pil
Publikováno v:
In Cell Reports Medicine 21 May 2024 5(5)
Downscaling aims to link the behaviour of the atmosphere at fine scales to properties measurable at coarser scales, and has the potential to provide high resolution information at a lower computational and storage cost than numerical simulation alone
Externí odkaz:
http://arxiv.org/abs/2105.08188
Bayesian optimisation (BO) uses probabilistic surrogate models - usually Gaussian processes (GPs) - for the optimisation of expensive black-box functions. At each BO iteration, the GP hyperparameters are fit to previously-evaluated data by maximising
Externí odkaz:
http://arxiv.org/abs/2105.00894
Batch Bayesian optimisation (BO) is a successful technique for the optimisation of expensive black-box functions. Asynchronous BO can reduce wallclock time by starting a new evaluation as soon as another finishes, thus maximising resource utilisation
Externí odkaz:
http://arxiv.org/abs/2010.07615
Bayesian optimisation is a popular approach for optimising expensive black-box functions. The next location to be evaluated is selected via maximising an acquisition function that balances exploitation and exploration. Gaussian processes, the surroga
Externí odkaz:
http://arxiv.org/abs/2004.08349
Bayesian optimisation is a popular, surrogate model-based approach for optimising expensive black-box functions. Given a surrogate model, the next location to expensively evaluate is chosen via maximisation of a cheap-to-query acquisition function. W
Externí odkaz:
http://arxiv.org/abs/2002.01873
The performance of acquisition functions for Bayesian optimisation to locate the global optimum of continuous functions is investigated in terms of the Pareto front between exploration and exploitation. We show that Expected Improvement (EI) and the
Externí odkaz:
http://arxiv.org/abs/1911.12809
Many expensive black-box optimisation problems are sensitive to their inputs. In these problems it makes more sense to locate a region of good designs, than a single-possibly fragile-optimal design. Expensive black-box functions can be optimised effe
Externí odkaz:
http://arxiv.org/abs/1904.11416