On the Determination of the Output Power in Mono/Multicrystalline Photovoltaic Cells

In the present work, two artificial intelligence-based models were proposed to determine output power of types photovoltaic cells including multicrystalline (multi-) and monocrystalline (mono-). Adaptive neuro-fuzzy inference system (ANFIS) Least-squares support vector machine (LSSVM) are applied for calculations. The estimation results very close actual data based on graphical statistical analysis. coefficients determination ( R 2 ) cell LSSVM ANFIS as 0.997 0.962, respectively. Additionally, multicells have id="M2"> values 0.999 0.995 ANFIS, acceptable id="M3"> various error parameters prove accuracy suggested models. visualization these comparisons clarifies compared with previously published learning methods. accurate performance in comparison others showed that our can be helpful tools power. Moreover, a sensitivity analysis effects inputs has been employed. shows light intensity more outcomes this study provide interesting which potential apply different parts renewable energy industries.