Reliability evaluation of two-stage evidence classification system considering preference and error

Qiang Liu

Reliability Engineering and System Safety, 2021, vol. 213, issue C

Abstract: In classic weighted voting systems (WVSs) and weighted voting classifiers (WVCs), the uncertainty in the system is characterized by probability theory, and the decisions of voting units are fused according to the majority rule. We use D-S evidence theory to improve the representation of the voting unit's decision and the fusion rule in WVSs and WVCs, and propose a new evidence classification system (ECS). In the ECS, a voting unit's decision is represented as a basic probability assignment function, the majority rule is replaced by the combination rule in D-S evidence theory. We also extend the WVS or WVC's decision-making process into two stages, and consider the measurement error and decision preference of the voting unit. A method based on Monte Carlo simulation is proposed to evaluate the reliability of the ECS. The effects of the number of voting units, decision preference and measurement error on the system reliability are also analyzed. Simulation results show that the introduction of evidence theory into ECS can effectively eliminate the effect of preference and error on system reliability.

Keywords: Weighted voting system; Evidence classification system; D-S evidence theory; Basic probability assignment; Weighted voting classifier; Decision preference; Sensing error; Reliability (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832021003082
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:213:y:2021:i:c:s0951832021003082

DOI: 10.1016/j.ress.2021.107783

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().