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A Predictive Model for the Population Growth of Refugees in Asia: A Multiple Linear Regression Approach

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Recent data provided by UNHCR indicated that 85% of the world’s displaced people are hosted in developing countries, while Asia and the Pacific are homes to about 3.5 million refugees. These hosting countries are often not well equipped with the resources needed to accommodate for the huge surplus in the number of refugees. The ability to predict the population growth of refugees thus enables refugee-hosting countries and NGOs to prepare for refugee migration beforehand, resulting in better infrastructure and opportunities for the refugees expected to enter a country. Advanced analytics could assist experts to chart where refugees are likely to head next, study the signs of future influx, prepare for reroute plans and raise crisis funds. In this paper, we present a regression model that predicts the anticipated number of refugee population in 20 Asian refugee-hosting countries. Using time-series analysis, we establish the pattern of refugee growth for Asian countries with a history of an average population of 2,000 refugees within the last 25 years as well as the last decade. Our model considers several input factors affecting the refugee population growth and predicts the number of refugees between 2017 to 2022 with promising results.
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Keywords: Predictive Analytics; Refugee Population; Refugees; Regression Model

Document Type: Research Article

Affiliations: Department of Computer Science, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, 53100 Kuala Lumpur, Malaysia

Publication date: March 1, 2019

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  • Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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