Prediction of uncertainty risk factors in engineering management system based on improved decision tree
Rong Tang,
Guoxiong Zhang and
Yunxia Li
International Journal of Industrial and Systems Engineering, 2023, vol. 44, issue 3, 285-301
Abstract:
In order to overcome the problem of low efficiency of the current prediction method for uncertainty risk factors in engineering management system, this paper proposes a prediction method for uncertainty risk factors in engineering management system based on improved decision tree. In this method, the reason model (accident causal model of complex system) and software, hardware, environment and livewar (SHEL) model are used to analyse the uncertainty risk factors in engineering management system, and the prediction system of uncertainty risk factors is established. The fuzzy clustering analysis method is used to judge the expert weight of risk factors, and the improved decision tree algorithm combined with the judgment results is used to predict the uncertainty risk factors in engineering management system. The simulation results show that the proposed method can reduce the prediction error rate by 1.5% in the following time.
Keywords: engineering management system; uncertainty; risk factors; improved decision tree; fuzzy clustering; prediction. (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=132259 (text/html)
Access to full text is restricted to subscribers.
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:ids:ijisen:v:44:y:2023:i:3:p:285-301
Access Statistics for this article
More articles in International Journal of Industrial and Systems Engineering from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().