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Sun, Junzi (author), Dijkstra, T.L.E. (author), Aristodemou, K. (author), Buzeţelu, V.S. (author), Falat, T. (author), Hogenelst, T.G. (author), Prins, N. (author), Slijper, B.C. (author)
In this paper, we propose open machine learning models that can provide airport delay predictions in a network with an error of around or less than five minutes. Due to the complexity of different components of air traffic networks, traditional flight performance model-based predictions fall short when dealing with numerous flights and often are...
conference paper 2022
document
van Gent, P. (author), Melman, T. (author), Farah, H. (author), Nes, Nicole Van (author), van Arem, B. (author)
The present study aims to add to the literature on driver workload prediction using machine learning methods. The main aim is to develop workload prediction on a multi-class basis, rather than a binary high/low distinction as often found in litearature. The presented approach relies on measures that can be obtained unobtrusively in the driving...
conference paper 2018