基于神经网络的岛国移民风险研究

Yong Gan, Fei Xue, Boqiao Zeng, Yuhua He, Q. Zhang, Jianghao Yu
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摘要

海平面上升是一种缓慢发生的自然灾害,具有累积性和渐进性。它对人类的生存、经济发展和文化传承有着相当大的影响[1]。再加上沿海许多地区地面沉降的影响,一个世纪内海平面上升可能达到1米甚至更高[2]。为了应对日益严峻的能源政策挑战,保护即将消失的独特文化,建立一个能够评估一个国家或地区是否存在移民风险的模型是很重要的。本文将建立一个神经网络模型,评估每个岛国的风险,预测其成为气候难民国家的可能性,以帮助世界各地的人们提前采取预防措施,帮助风险国家提前为移民国民做好准备。并通过进一步分析联合国难民事务高级专员办事处在叙利亚确定的11个国家的数据,进行模型构建和模型计算[3]。最后,根据11个国家的人口分布不平衡指数和人口密度集中指数[4]可知,在波黑,叙利亚难民文化流失的风险相对较低。
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Research on Migration Risk of Island Countries Based on Neural Network
Sea level rise is a slow-onset natural disaster, with cumulative and gradual nature. It has a considerable impact on human survival, economic development and cultural inheritance [1]. Coupled with the impact of land subsidence in many areas along the coast, sea level rise may reach 1 meter or even higher within a century [2]. In order to meet the increasingly severe energy policy challenges and protect the unique culture that is about to disappear, it is important to establish a model that can assess whether a country or region has migration risks. This article will build a neural network model to assess the risk of each island country and predict its possibility of becoming a climate refugee country, in order to help people around the world to take precautionary measures in advance, and help risky countries prepare for migrating nationals in advance. And through further analysis of the data of 11 countries that have been determined by the Office of the United Nations High Commissioner for Refugees in Syria, the model construction and model calculation are carried out [3]. Finally, according to the imbalanced population distribution index and population density concentration index of 11 countries [4], we can know that in Bosnia and Herzegovina the risk of losing the culture of Syrian refugees is relatively low.
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