.png){kind=icon}
返回
minStab: Stable Network Evolution Rule Mining for System Changeability Analysis
.png){kind=icon}
PRE
AI
DOI：10.1109/TETCI.2019.2892734.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Growing number of evolving systems creates demand for system evolution analytics with modern computational intelligence algorithms and tools. In this paper, we introduce new measures of stability and changeability for system evolution analysis over time. We proposed a Stable Network Evolution Rule Mining and a Changeability Metric for an evolving system. For this, we use two different characteristics of Network Evolution Rules (NERs). First, given a network of a system state Si, we call an NER interesting in Si if its support and confidence exceed given thresholds (minimum support and minimum confidence). Second, given a set of networks for a set of states (SS), we define the stability of an NER to be the percentage of states in SS in which the rule is interesting. We call an NER stable in SS if its stability exceeds a given threshold named as minimum stability (minStab). Based on this, we developed an intelligent tool, which is used for experiments on evolving systems. We applied our approach to a number of real-world systems including: software system, natural language system, retailmarket system, and IMDb system. It results Stable NERs and Changeability Metric value for each evolving system.
Keyword:
Stability analysis
Data mining
Measurement
Tools
Silicon
Databases
Software systems
Systems engineering and theory
data mining
association rules
network theory (graphs)
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
I
IF:
6.5
论文数:
1.4K
被引数:
4.5K
机构
引用论文
.png){kind=icon}
分享收藏
分享收藏Transitioning Systems Thinking to Model-Based Systems Engineering: Systemigrams to SysML Models
PREAI
分享收藏
分享收藏
查看更多内容