通过数据挖掘增强信息物理系统的可靠性

T. Sanislav, Karla Merza, G. Mois, L. Miclea
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引用次数: 7

摘要

本文提出的研究解决了在网络物理系统中使用数据挖掘技术来增强可靠性特征的问题。一个用于环境监测的信息物理系统被认为是一个案例研究。在这种情况下,数据挖掘的主要任务是预测由于硬件和软件组件故障而导致的传感器值缺失。基于一种众所周知的数据挖掘方法,在案例研究系统上测试了不同版本的数据挖掘回归算法。测试结果表明,所考虑的算法能够以满意的精度预测传感器数据,从而降低了系统的故障率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cyber-physical system dependability enhancement through data mining
The research presented in the current paper addresses the use of data mining techniques for enhancing the dependability characteristic in the case of cyber-physical systems. A cyber-physical system for environmental monitoring was considered as a case study. In this context, the main task of data mining is to predict the missing sensor values caused by hardware and software components malfunctions. Different versions of a data mining regression algorithm were tested on the case study system, based on a well known data mining methodology. The test results show that the algorithms taken into consideration can predict sensor data with satisfactory accuracy, leading to a decreased failure rate of the system.
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