TY - JOUR ID - 70093 TI - Estimation of Global Solar Irradiance Using a Novel combination of Ant Colony Optimization and Empirical Models JO - Journal of Renewable Energy and Environment JA - JREE LA - en SN - 2423-5547 AU - Lashkar Ara, Afshin AU - hosseini, rahil AU - Bagheri Tolabi, Hajar AD - Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran AD - Department of Computer Engineering, Shahr‐e‐Qods Branch, Islamic Azad University, Tehran, Iran AD - Department of Electrical Engineering, Khorramabad Branch, Islamic Azad University, Khorramabad, Iran Y1 - 2016 PY - 2016 VL - 3 IS - 3 SP - 59 EP - 66 KW - Ant colony optimization (ACO) KW - Empirical Models KW - Global solar irradiance KW - Intelligent models DO - 10.30501/jree.2016.70093 N2 - In this paper, a novel approach for the estimation of global solar irradiance is proposed based on a combination of empirical correlation and ant colony optimization. Empirical correlation has been used to estimate monthly average of daily global solar irradiance on a horizontal surface. The Ant Colony Optimization (ACO) algorithm has been applied as a swarm-intelligence technique to tune the coefficients of linear and nonlinear empirical models. . The performance of the models is investigated for the estimation of global solar irradiance at four different climatic regions of Iran based on statistical indicators like coefficient of determination (R2) and root mean square error (RMSE). The results obtained from the proposed model are superior in comparison with the other well established models. UR - https://www.jree.ir/article_70093.html L1 - https://www.jree.ir/article_70093_2d91f13804f1c73fd57f348b12f14cda.pdf ER -