Article citationsMore>>

Yang, C.W., Li, Z.H., Guo X.Y., Yu, W.Y., Jin, J. and Zhu, L. (2019) Application of BP Neural Network Model in Risk Evaluation of Railway Construction. Complexity, 2019, Article ID: 2946158.
https://doi.org/10.1155/2019/2946158

has been cited by the following article:

• TITLE: Study on the Macro-Level Risk Assessment and Intelligent Line Selection for Overseas Railway Construction

  AUTHORS: Jing Lian, Jing Jin, Zonghao Li

  KEYWORDS: Railway Route Selection, Principal Component Analysis Method, Risk Assessment

  JOURNAL NAME: American Journal of Industrial and Business Management, Vol.9 No.11, November 28, 2019

  ABSTRACT: In recent years, China has made overseas railway construction a key investment project. The primary task of overseas railway investment construction is to select railway routes. Taking some sections of the Belt and Road as an example, 15 representative risk indicators have been established based on the survey data. Based on the principal component analysis method, the risk assessment is carried out in 63 countries along the Belt and Road district, and finally the risk scores are sorted, and the reasonable high-speed rail lines are programmed through the ranking of risk scores.