Back
 AJIBM  Vol.9 No.11 , November 2019
Study on the Macro-Level Risk Assessment and Intelligent Line Selection for Overseas Railway Construction
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.
Cite this paper: Lian, J. , Jin, J. and Li, Z. (2019) Study on the Macro-Level Risk Assessment and Intelligent Line Selection for Overseas Railway Construction. American Journal of Industrial and Business Management, 9, 2064-2077. doi: 10.4236/ajibm.2019.911136.
References

[1]   Zhu, Y. (2009) Innovation and Practice on Railway Location Concept. Journal of Railway Engineering Society, 26, 1-5.

[2]   Liu, W.M. (2002) Research on Main Engineering Economics Problems of Chinese High-Speed Passenger-Only Guided Transport System. Southwest Jiaotong University, Chengdu.

[3]   Yang, H. (2013) The Application of Clustering Analysis Based on SPSS in Industry Statistical Data. Jilin University, Changchun.

[4]   Jin, J. (2019) Research on Risk Evaluation of International Railway Corridors Construction among Countries along “The Belt and Road”. China Academy of Railway Sciences, Beijing.

[5]   Jia, R.N. (2015) The Study on the Country Risk Assessment and Control Based on Bank. University of International Business and Economics, Beijing.

[6]   Wang, J.P. and Wang, N. (2016) Financial Risk Assessment of China’s Energy Listed Companies—Based on Principal Component Analysis. Friends of Accounting, 11, 60-66.

[7]   Huang, A., Yang, L.A. and Du, T. (2014) Comprehensive Assessment of Soil Nutrients Based on PCA. Arid Zone Research, 31, 819-825.

[8]   Chen, P. (2014) Principal Component Analysis and Its Application in Feature Extraction. Shanxi Normal University, Xi’an.

[9]   Cui, Y.P. and Wu, J.Y. (2017) Study on Increasing Operation Quality of China Railway Express by Using Asia-Europe Railway Transpor Corridor. Railway Transport and Economy, 39, 68-72.

[10]   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

[11]   Jin, J., Li, Z.H., Zhu, L. and Yang, C.W. (2019) A Research on Risk Assessment of China Railway “Go-Global” Project Construction. Railway Transport and Economy, 41, 86-91.

[12]   Jin, J., Zhu, L., Li, Z.H., Tong X.H. and Yang, C.W. (2019) Application of Variable Structure of BPNN in Risk Evaluation of Overseas Railway Construction in Target Countries. Journal of the China Railway Society, 40, 7-12.

[13]   Jin J., Li Z.H., Zhu L., Tong X.H. and Yang C.W. (2019) Application of BP Neural Network in Risk Evaluation of Railway Construction. Journal of Railway Engineering Society, 36, 106-112.

 
 
Top