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Combining Diffusion Models and Macroeconomic Indicators with a Modified Genetic Programming Method: Implementation in Forecasting the Number of Mobile Telecommunications Subscribers in OECD Countries

机译:用改进的遗传编程方法结合扩散模型和宏观经济指标:在经合组织国家的移动电信用户数量预测中的实施

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摘要

This paper proposes a modified Genetic Programming method for forecasting the mobile telecommunications subscribers’ population. The method constitutes an expansion of the hybrid Genetic Programming (hGP) method improved by the introduction of diffusion models for technological forecasting purposes in the initial population, such as the Logistic, Gompertz, and Bass, as well as the Bi-Logistic and LogInLog. In addition, the aforementioned functions and models expand the function set of hGP. The application of the method in combination with macroeconomic indicators such as Gross Domestic Product per Capita (GDPpC) and Consumer Prices Index (CPI) leads to the creation of forecasting models and scenarios for medium- and long-term level of predictability. The forecasting module of the program has also been improved with the multi-levelled use of the statistical indices as fitness functions and model selection indices. The implementation of the modified-hGP in the datasets of mobile subscribers in the Organisation for Economic Cooperation and Development (OECD) countries shows very satisfactory forecasting performance.
机译:本文提出了一种预测移动电信用户群体改良遗传编程方法。该方法构成了通过引入扩散模型的用于技术预测的目的在初始种群,如物流,贡佩尔茨,和贝斯,以及碧Logistic和LogInLog改善混合遗传编程(HGP)方法的扩展。此外,上述功能和模式扩展功能集HGP的。该方法的结合宏观经济指标如人均国内生产总值(GDPPC)和消费者价格指数(CPI)导致建立预测模型和场景的中期和可预测的长期水平的应用。该方案的预测模块也已与多层次的使用统计指标作为健身的功能和模式选择指数提高。经修改人类基因组计划在组织,经济合作与发展组织(OECD)国家的表演非常满意的业绩预测移动用户的数据集执行。

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