Title: Prediction of uncertainty risk factors in engineering management system based on improved decision tree

Authors: Rong Tang; Guoxiong Zhang; Yunxia Li

Addresses: Department of Railway Engineering and Civil Engineering, Shandong Polytechnic, Jinan 250104, China ' Shandong Highway Designing and Consulting CO., LTD. Jinan 250102, China ' Department of Railway Engineering and Civil Engineering, Shandong Polytechnic, Jinan 250104, China

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.

DOI: 10.1504/IJISE.2023.132259

International Journal of Industrial and Systems Engineering, 2023 Vol.44 No.3, pp.285 - 301

Received: 08 May 2021
Accepted: 12 Jul 2021
Published online: 14 Jul 2023 *

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