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    Predictions on Flexible CdTe Solar Cell Performances by Artificial Neural Networks
    (2023) Ganbarova, Sevinj; Akkoyun, Serkan; Mamedov, Vusal; Mamedov, Huseyn
    CdTe solar cells on ultra-thin glass substrates are light and flexible. Flexible cells are widely preferred modules in technological fields. The flexibility of these cells enables them to cope with deformations. The efficiency of these has reached 19%. In this work, we used artificial neural network (ANN) method for the determination the performance of flexible CdTe solar cells despite bending and time. The performances of the solar cell before and after bending have been predicted. According to the results from the ANN calculations using the experimental data in the literature, MSE values of ANN estimates range from 0.06% to 0.28%.