A hybrid computational approach to estimate solar global radiation: An empirical evidence from Iran

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@Article{Mostafavi:2013:Energy,

• author = "Elham Sadat Mostafavi and Sara Saeidi Ramiyani and Rahim Sarvar and Hashem Izadi Moud and Seyyed Mohammad Mousavi",
• title = "A hybrid computational approach to estimate solar global radiation: An empirical evidence from Iran",
• journal = "Energy",
• volume = "49",
• month = "1 " # jan,
• pages = "204--210",
• year = "2013",
• keywords = "genetic algorithms, genetic programming, Solar global radiation, Hybrid method, Simulated annealing, Prediction",
• ISSN = "0360-5442",
• DOI = "doi:10.1016/j.energy.2012.11.023",
• URL = "http://www.sciencedirect.com/science/article/pii/S0360544212008845",
• abstract = "This paper presents an innovative hybrid approach for the estimation of the solar global radiation. New prediction equations were developed for the global radiation using an integrated search method of genetic programming (GP) and simulated annealing (SA), called GP/SA. The solar radiation was formulated in terms of several climatological and meteorological parameters. Comprehensive databases containing monthly data collected for 6 years in two cities of Iran were used to develop GP/SA-based models. Separate models were established for each city. The generalisation of the models was verified using a separate testing database. A sensitivity analysis was conducted to investigate the contribution of the parameters affecting the solar radiation. The derived models make accurate predictions of the solar global radiation and notably outperform the existing models.",

}

Genetic Programming entries for Elham Sadat Mostafavi Sara Saeidi Ramiyani Rahim Sarvar Hashem Izadi Moud Seyyed Mohammad Mousavi

Citations