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A web-based system to determine risk of investment in international rail construction projects

Manual evaluation of investment risk make results and solutions are not timely. The objective of the study is to explore intelligent risk data collecting and risk early warning of international rail construction. First, this study has identified risk variables by content mining. Second, risk thresho...

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Autor principal: Yuan, Ting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196323/
https://www.ncbi.nlm.nih.gov/pubmed/37208406
http://dx.doi.org/10.1038/s41598-023-34358-7
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author Yuan, Ting
author_facet Yuan, Ting
author_sort Yuan, Ting
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description Manual evaluation of investment risk make results and solutions are not timely. The objective of the study is to explore intelligent risk data collecting and risk early warning of international rail construction. First, this study has identified risk variables by content mining. Second, risk thresholds are calculated by the quantile method based on data from 2010 to A.D. 2019. Third, this study has developed risk early warning system by the gray system theory model, the matter-element extension method and the entropy weight method. Fourth, the risk early warning system is verified using Nigeria coastal railway project in Abuja. This study found that: (1) the framework of the developed risk warning system contains a software and hardware infrastructure layer, a data collection layer, an application support layer, and an application layer. (2) 37 investment risk variables are recognized; (3) 12 risk variables thresholds intervals are not equally divided between 0 and 1, the others are evenly distributed; (4) based on the application of Nigeria coastal railway project in Abuja, the system verification results are consistent with real situations, which is shown that risk early warning system is reasonable and feasible. These findings offer a good reference for intelligent risk management.
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spelling pubmed-101963232023-05-21 A web-based system to determine risk of investment in international rail construction projects Yuan, Ting Sci Rep Article Manual evaluation of investment risk make results and solutions are not timely. The objective of the study is to explore intelligent risk data collecting and risk early warning of international rail construction. First, this study has identified risk variables by content mining. Second, risk thresholds are calculated by the quantile method based on data from 2010 to A.D. 2019. Third, this study has developed risk early warning system by the gray system theory model, the matter-element extension method and the entropy weight method. Fourth, the risk early warning system is verified using Nigeria coastal railway project in Abuja. This study found that: (1) the framework of the developed risk warning system contains a software and hardware infrastructure layer, a data collection layer, an application support layer, and an application layer. (2) 37 investment risk variables are recognized; (3) 12 risk variables thresholds intervals are not equally divided between 0 and 1, the others are evenly distributed; (4) based on the application of Nigeria coastal railway project in Abuja, the system verification results are consistent with real situations, which is shown that risk early warning system is reasonable and feasible. These findings offer a good reference for intelligent risk management. Nature Publishing Group UK 2023-05-19 /pmc/articles/PMC10196323/ /pubmed/37208406 http://dx.doi.org/10.1038/s41598-023-34358-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Yuan, Ting
A web-based system to determine risk of investment in international rail construction projects
title A web-based system to determine risk of investment in international rail construction projects
title_full A web-based system to determine risk of investment in international rail construction projects
title_fullStr A web-based system to determine risk of investment in international rail construction projects
title_full_unstemmed A web-based system to determine risk of investment in international rail construction projects
title_short A web-based system to determine risk of investment in international rail construction projects
title_sort web-based system to determine risk of investment in international rail construction projects
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196323/
https://www.ncbi.nlm.nih.gov/pubmed/37208406
http://dx.doi.org/10.1038/s41598-023-34358-7
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