A method of judging the sustainability of a country based on SVM

This paper explains and demonstrates how to distinguish between sustainable countries and unsustainable ones by using sport vector machine (SVM). There are many methods to analyze and judge the sustainability at home and abroad. However, considering that there only exists methods to judge the sustainability of a country according to one indicator, I come up with a quantitative and comprehensive model to analyze the sustainability of a country. Firstly, I choose nine indicators which include life expectancy at birth, food production index, improved water source, unemployment (of total labor), GDP per capita, poverty headcount ratio, electric power consumption (kwh per capita), CO2 emissions (metric tons per capita) and forest area (% of land area). And the indicators I choose cover four aspects: economy, environment, resource and society, which can approximately represent the sustainability of a country. Then use the selected eight countries whose sustainability is clear to get the hyper plane of sport vector machine. Finally, use the method to classify another ten countries. The result of classification is consistent with the actual situation, which shows the accuracy of the model. I use a lot of experimental data to prove the accuracy and rationality of the model. The model in the paper helps us to obtain the sustainability of a country.