National Vulnerability Assessment System: Part 2 Model Testing

DOI

10.2991/tlicsc-18.2018.57How to use a DOI?

Keywords

Climate change, NVAS, grey relational analysis, regression analysis.

Abstract

In order to further determine the impact of climate change on national vulnerabilities, we choose Yemen as the study object. On the one hand, we select some countries that have been in an extremely fragile state for a long time as a reference standard. With method of Grey Relational Analysis, we calculate rational grade of each metric by use of related data collected from the World Bank. On the other hand, we use regression analysis to find the regression equation between climate change and the four indicators. The results show that the lack of precipitation and high temperature in Yemen has largely affected the second-class indicators, thereby increasing the country's vulnerability. in the case of Yemen, we have put forward some interventions and analyzed how these measures can effectively prevent a country from becoming a vulnerable country. Finally, we test the sensitivity of our model, conclude the strengths and weakness. And we discuss the applicability of the model to states of different sizes. We conclude that the model is applicable in smaller states and not in larger states, and improve the model.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Fengshan Song
PY  - 2018/12
DA  - 2018/12
TI  - National Vulnerability Assessment System: Part 2 Model Testing
BT  - Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)
PB  - Atlantis Press
SP  - 359
EP  - 363
SN  - 1951-6851
UR  - https://doi.org/10.2991/tlicsc-18.2018.57
DO  - 10.2991/tlicsc-18.2018.57
ID  - Song2018/12
ER  -