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Impact and Suggestions of Sea Level Rise on the Survival of Tuvalu: Evidence from Mathematical and Computer Modeling
Author(s) -
Hengyi Yang,
Mengnan Hou,
Aoran Cui
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/514/3/032028
Subject(s) - population , refugee , analytic hierarchy process , diversity (politics) , hierarchy , geography , operations research , development economics , economics , political science , engineering , demography , sociology , market economy , archaeology , law
Existing research indicates that many countries are in danger of disappearing completely due to sea level rise. Therefore, many environmentally displaced persons (EDPs) will be generated. The number of these EDPs and the ways of resettling with humanitarianism are promising issues. Tuvalu is the fourth smallest country in the world, and its country has stated that it has plans to relocate the country, so it has attracted our attention. Firstly, assuming that the population of the area is not affected by sea level, establish block population growth model, predict the future normal population. At the same time, build the prediction model of BP neural network based on EMD to predict the future sea level, and the connection between the two models is time. When the sea level reaches a certain threshold, the area’s environment is no longer stable, and in this time the year when the threshold was reached and the corresponding population were determined. We use the analytic hierarchy process to evaluate the influences of various social policies on cultural loss risk, which can effectively adjust the policy and protect the diversity of culture. Accepting refugees to the society, economy and culture of a country is a great challenge. Later, we set up the secondary fuzzy comprehensive evaluation model, and a lot of impact factors are classified as economic, social, ecological and other categories. Standardize and normalize the data. Using the entropy weight method to determine the weight of each index. Give a score for every country, and countries or regions of high scores have the ability to accept the refugees. Last, we use the analytic hierarchy process to evaluate the influences of various social policies on cultural loss risk, which can effectively adjust the policy and protect the diversity of culture.

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