decision-making model under risk assessment based on entropy
Clicks: 202
ID: 167893
2016
Article Quality & Performance Metrics
Overall Quality
Improving Quality
0.0
/100
Combines engagement data with AI-assessed academic quality
Reader Engagement
Steady Performance
30.0
/100
202 views
1 readers
Trending
AI Quality Assessment
Not analyzed
Abstract
Decision-making under risk assessment involves dealing with the matter of uncertainty, especially in projects such as tunnel construction. Risk control should include not only measures to reduce the possible consequence of incident, but also exploration measures (information collecting measures) to reduce the uncertainty of the incident. The classical risk assessment model in engineering is R = P × C which only takes account of the assessment and decision-making of possible consequences. It cannot provide theoretical guidance for taking exploration measures. The paper presents an advanced methodology to assess the effectiveness of exploration measures in decision-making. The methodology classifies risk into two attributes: hazard (expected value) and uncertainty (entropy). On this basis, a generalized model of decision-making under risk assessment is proposed. This model extends the use of the classical assessment model to a more general case. The reason for taking exploration measures and assessment of such measures’ effectiveness could be explained well by this developed model. This model can also serve as a descriptive model for many risk problems and provide a decision-making basis for a variety of risk types. Moreover, the assessment process and calculation method are applied with some case studies.Reference Key |
dong2016entropydecision-making
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
---|---|
Authors | ;Xin Dong;Hao Lu;Yuanpu Xia;Ziming Xiong |
Journal | European journal of medicinal chemistry |
Year | 2016 |
DOI | 10.3390/e18110404 |
URL | |
Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.