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相关概念视频

Run Charts01:12

Run Charts

41
Run charts serve as an essential instrument for visualizing the performance of various processes over time, enabling the identification of trends and patterns crucial for quality improvement. These charts map out a series of data points chronologically, offering insights into the stability and efficiency of a process. A run chart's creation involves plotting data points on a graph, with the time intervals on the horizontal axis and the specific measurements on the vertical axis. For...
41
Interpreting Run Charts01:25

Interpreting Run Charts

50
Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...
50
Taping Over Different Ground Profiles01:12

Taping Over Different Ground Profiles

21
Taping over varying ground profiles requires careful adaptation to achieve accurate measurements. On smooth, level ground with minimal vegetation, the tape can rest directly on the ground. Here, the taping team, typically consisting of a head and a rear tapeman, coordinates their positions with clear communication. The rear tapeman holds the tape at the starting point and guides the head tapeman toward a range pole placed beyond the endpoint, using hand or voice signals to ensure alignment.On...
21

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评估过程采矿技术的基础真相方法.

Dominique Sommers1, Natalia Sidorova1, Boudewijn van Dongen1

  • 1Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, the Netherlands.

Process science
|March 26, 2025
PubMed
概括

为了评估过程挖矿技术,生成现实的合成过程数据与基本真相至关重要. 我们的新方法创建不完美的事件日志和偏离模型,提供比传统方法更深入的见解.

科学领域:

  • 计算机科学 计算机科学
  • 信息系统信息系统信息系统

背景情况:

  • 评估过程挖掘技术与现实世界的数据是具有挑战性的,因为缺少的基础真相和数据不完美.
  • 现有的合成数据生成方法往往无法捕获现实的行为偏差,并失去模型日志链接.

研究的目的:

  • 为生成现实的合成过程数据提出一个基本真相方法,包括行为偏差和记录错误.
  • 通过提供基础真相知识,使工艺采矿技术能够进行可靠的评估.

主要方法:

  • 从初始工艺模型 (自动或手工制作) 生成合成工艺数据.
  • 整合行为偏差的模式和记录错误,以创建偏差模型和不完美的事件日志.
  • 使用初始模型,偏差模型和不完美的日志进行评估.

主要成果:

  • 在三个合成过程数据集上演示了方法.
  • 在符合性检查用例中应用生成的数据来评估系统对齐.
  • 展示了暴露和解释模拟和记录行为之间的偏差的能力.

结论:

  • 与传统方法相比,拟议的基础真相方法为工艺采矿技术的性能提供了卓越的定量和定性见解.
  • 这种方法通过模拟现实的缺陷来增强对工艺采矿技术的优缺点的理解.
关键词:
行为模式 行为模式评价 评价 评价现实的噪音 现实的噪音合成过程数据 合成过程数据验证 验证 验证 验证

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