论文标题
各向异性：大气对流的视觉指导经验模型
IsoTrotter: Visually Guided Empirical Modelling of Atmospheric Convection
论文作者
论文摘要
自然科学中经常使用适合于观测数据的数据的经验模型来描述身体行为和支持发现。但是，使用更复杂的模型，参数的回归很快就变得不足，需要视觉参数空间分析以了解和优化模型。在这项工作中，我们提出了一项设计研究，用于构建描述大气对流的模型。我们提出了一种混合定量方法，用于视觉引导建模，将交互式视觉参数分析与部分自动参数优化整合在一起。我们的方法包括一种新的半自动技术，称为各向异性技术，我们通过沿模型的等音室进行导航来优化过程。我们根据旁流板器的飞行轨迹的独特观察数据来评估模型。
Empirical models, fitted to data from observations, are often used in natural sciences to describe physical behaviour and support discoveries. However, with more complex models, the regression of parameters quickly becomes insufficient, requiring a visual parameter space analysis to understand and optimize the models. In this work, we present a design study for building a model describing atmospheric convection. We present a mixed-initiative approach to visually guided modelling, integrating an interactive visual parameter space analysis with partial automatic parameter optimization. Our approach includes a new, semi-automatic technique called IsoTrotting where we optimize the procedure by navigating along isocontours of the model. We evaluate the model with unique observational data of atmospheric convection based on flight trajectories of paragliders.
