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  1. Xu X, Rogers RA
    PLoS One, 2023;18(3):e0275625.
    PMID: 36893159 DOI: 10.1371/journal.pone.0275625
    After the cold war, some countries gradually seek to regional cooperation when they could not handle various transnational challenges alone. Shanghai Cooperation Organization (SCO) is a good example. It brought Central Asian countries together. This paper applies the text-mining method, using co-word analysis, co-occurrence matrix, cluster analysis, and strategic diagram to analyze the selected articles from newspapers quantitatively and visually. In order to investigate the Chinese government's attitude toward the SCO, this study collected data from the China Core Newspaper Full-text Database, which contains high-impact government newspapers revealing the Chinese government's perception of the SCO. This study characterizes the changing role of SCO as perceived by the Chinese government from 2001 to 2019. Beijing's changing expectations in each of the three identified subperiods are described.
  2. Xu X, Rogers RA, Estrada MAR
    Comput Econ, 2022 Sep 20.
    PMID: 36157278 DOI: 10.1007/s10614-022-10311-0
    With the development of economic and technologies, the trend of annual Gross Domestic Product (GDP) and carbon dioxide (CO2) emission changes with time passes. The relationship between economic growth and carbon dioxide emissions is considered as one of the most important empirical relationships. In this study, we focus on the member of Shanghai Cooperation Organization, including China, Russia, India, and Pakistan and collect CO2 emission and annual GDP from 1969 to 2014. The statistical methods and tests are used to find the relationship between annual GDP and CO2 emission in these countries. Based on relationship between annual and CO2 emission, a novel multi-step prediction algorithm called Extreme Learning Machine with Artificial Bee Colony (ELM-ABC) is proposed for forecasting annual GDP based on CO2 emission and historical GDP features. According to the experimental results, it proved that the proposed model had a super forecasting ability in GDP prediction and it could predict ten-year future annual GDP for the corresponding countries. Moreover, the forecasting results showed that the annual GDP of China and Pakistan will continue to grow but growth will slow after 2025. The annual GDP in India will exhibit unstable growth. The trend of Russia will follow the pattern between 2010 and 2016.
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