有约束的建模测量技术问题

G. Roman, T. Dobrowiecki
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引用次数: 1

摘要

跨学科的应用为测量领域带来了新的有趣但又困难的问题。这样的应用总体上强调了测量过程的自动化。对实验如何计划、控制、评估等的分析。将重点放在与测量相关的专家知识如何在自主智能测量系统的开发中得到表现和利用的问题上。人工智能(AI)领域开发的方法自然适合此类应用。本文提出了所谓的约束作为建模测量的知识表示工具。当需要测量过程背后的更深层次的现象模型时,考虑到它们如何很好地表达物理系统的不同子系统和状态变量之间的依赖关系,应用约束作为知识表示可能是富有成效的。作者回顾了适合于基于约束的知识表示的度量技术问题,分析了实际约束满足问题的需求,并从该角度评价了已知的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling measurement technical problems with constraints
Interdisciplinary applications exposed new interesting, but difficult problems in the field of measurement. Such applications put emphasis on the automation of the measurement process on the whole. The analysis of how the experiments are planned, controlled, evaluated, etc. Brought into focus the question of how well the expert knowledge related to the measurement can be represented and utilised in the development of autonomous intelligent measurement systems. Methods developed in the field of Artificial Intelligence (AI) lend themselves naturally for such applications. The present paper proposes so called constraints to be used as the knowledge representation tool in modelling measurements. When a deeper model of the phenomena underlying the measurement processes is needed, applying constraints as knowledge representation is potentially fruitful, considering how well they express the dependencies between different subsystems and state variables of the physical systems. Authors review measurement technical problems suited for the constraint based knowledge representation, analyse the requirements of the actual constraint satisfaction problems and evaluate the known methodology from that perspective.<>
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