Multi-dimensional parameter-space partitioning of spatio-temporal simulation ensembles

نویسندگان

چکیده

Numerical simulations are commonly used to understand the parameter dependence of given spatio-temporal phenomena. Sampling a multi-dimensional space and running respective leads an ensemble large number simulation runs. A main objective for analyzing is partition (or segment) into connected regions runs with similar behavior. To facilitate such analysis, we propose novel visualization method parameter-space partitions. Our based on concept hyper-slicer, which allows undistorted views segments’ extent transitions. For navigation within space, interactions 2D embedding samples, including their segment memberships, supported. Parameter-space partitions generated in semi-automatic fashion by similarity ensemble’s Clusters induce segments partition. We link partitioning visualizations similarity-space embed them interactive visual analysis tool that supports all facets targeted at overarching goal partitioning. The can then be visually analyzed interactively refined. compared our approach alternative methods evaluated it experts case studies from three different domains.

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ژورنال

عنوان ژورنال: Computers & Graphics

سال: 2022

ISSN: ['0097-8493', '1873-7684']

DOI: https://doi.org/10.1016/j.cag.2022.04.005