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Trajectory prediction is the core module of modern air traffic management system. Focused on the trajectory prediction model and key algorithm of the system, this paper tries to overcome the disadvantages of the traditional linear prediction method via employing machine learning technology in the problem. The statistical historical flight data of different aircraft type is taken as the training sample...
Semi-supervised learning and active learning are important techniques to build more accurate model while labeled data are scarce. The objective of this paper is combining both to effectively relieve user labor for multi-class annotation. We propose a novel graph-based active semi-supervised learning framework which aim at efficiently learning a multi-class model with minimal human labor. In particular,...
Understanding the spatial distribution of fine particle sulfate (SO42-) concentrations is important for optimizing emission control strategies and assessing the population health impact due to exposure to SO42-. Aerosol remote sensors aboard polar orbit satellites can help expand the sparse ground monitoring networks into regions currently not covered. We developed a generalized additive model (GAM)...
Web hot topic prediction is now one of the most significant research focus in Web data mining, which can reflect the Internet users' psychosocial predilection, may greatly benefit us. Markov and neural network are such two typical traditional prediction model, however, the Markov method can neither capture nor express the statistical property of the real data while the computation of neural network...
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