Skip to main navigation Skip to search Skip to main content

Gradient computations and geometrical meaning of importance measures

  • Northwestern Polytechnical University Xian

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Reliability importance is a scalar which is a partial derivative of system reliability function with respect to component reliability variable. Gradient is a vector consisting of partial derivatives of one continuous function with respect to all variables and gradient direction points in the direction of the greatest rate of the function increase. In order to analyze the direction that the system performance rises most quickly, this paper studies the gradient computations and geometrical meaning of importance measures. The expressions and physical meaning of importance measures are described at first. Then, the representations of importance measures in gradient are introduced, and relationships between importance measures and gradient are analyzed. Thirdly, the characteristics and geometrical meaning of gradient representations of importance measures are discussed. Finally, numerical examples in typical systems are demonstrated to verify the representation methods of importance measures in gradient.

Original languageEnglish
Pages (from-to)305-318
Number of pages14
JournalQuality Technology and Quantitative Management
Volume10
Issue number3
DOIs
StatePublished - Sep 2013

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • Geometrical meaning
  • Gradient
  • Importance measures
  • Partial derivative
  • System performance.

Fingerprint

Dive into the research topics of 'Gradient computations and geometrical meaning of importance measures'. Together they form a unique fingerprint.

Cite this