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

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@Article{journals/advor/SalpasaranisSK14,
  author =       "Konstantinos Salpasaranis and Vasilios Stylianakis and 
                 Stavros Kotsopoulos",
  title =        "Combining Diffusion Models and Macroeconomic
                 Indicators with a Modified Genetic Programming Method:
                 Implementation in Forecasting the Number of Mobile
                 Telecommunications Subscribers in {OECD} Countries",
  journal =      "Advances Operations Research",
  year =         "2014",
  volume =       "2014",
  keywords =     "genetic algorithms, genetic programming",
  bibdate =      "2014-07-08",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/journals/advor/advor2014.html#SalpasaranisSK14",
  URL =          "http://dx.doi.org/10.1155/2014/568478",
  URL =          "http://downloads.hindawi.com/journals/aor/2014/568478.pdf",
  size =         "20 pages",
  abstract =     "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.",
}

Genetic Programming entries for Konstantinos Salpasaranis Vasilios Stylianakis Stavros Kotsopoulos

Citations