自然环境的数字孪生体。
Digital twins of the natural environment.
作者信息
Blair Gordon S
机构信息
School of Computing and Communications, Lancaster University, Lancaster, UK.
出版信息
Patterns (N Y). 2021 Oct 8;2(10):100359. doi: 10.1016/j.patter.2021.100359.
Abstract
Digital twins emerged in the field of engineering but are now being applied in many areas of study. This article reflects on the enormous potential of digital twins of the natural environment and proposes an approach that builds on the massive legacy of process model understanding in this area combined with new insights from data understanding, including from AI/machine learning.
摘要
数字孪生起源于工程领域，但如今正应用于许多研究领域。本文探讨了自然环境数字孪生的巨大潜力，并提出了一种方法，该方法基于该领域过程模型理解的大量遗产，并结合了数据理解（包括来自人工智能/机器学习的数据理解）的新见解。
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