The power output forecasting of the photovoltaic (PV) system is essential before deciding to install a photovoltaic system in Nakhon Ratchasima, Thailand, due to the uneven power production and unstable data. This research simulates the power output forecasting of PV systems by using adaptive neuro-fuzzy inference systems (ANFIS), comparing accuracy with particle swarm optimization combined with artificial neural network methods (PSO-ANN). The simulation results show that the forecasting with the ANFIS method is more accurate than the PSO-ANN method. The performance of the ANFIS and PSO-ANN models were verified with mean square error (MSE), root mean square error (RMSE), mean absolute error (MAP) and mean absolute percent error (MAPE). The accuracy of the ANFIS model is 99.8532%, and the PSO-ANN method is 98.9157%. The power output forecast results of the model were evaluated and show that the proposed ANFIS forecasting method is more beneficial compared to the existing method for the computation of power output and investment decision making. Therefore, the analysis of the production of power output from PV systems is essential to be used for the most benefit and analysis of the investment cost.

The system of lead free piezoelectric ceramics, (1-x)(0.94Bi_0.5Na_0.5TiO₃-0.06BaTiO₃)-xBaSnO₃ [abbreviated as BNT-BT-xBSn] with the compositions, x = 0.00, 0.02, 0.04, 0.06, 0.08 and 0.10 was synthesized via the conventional solid state reaction method. All the products from X-ray diffraction patterns showed diffraction peaks as a phase perovskite structure, with no secondary phases. Due to the composition-dependence of the ferroelectric, bipolar and unipolar strain properties were investigated in order to achieve a good new lead free piezoelectric ceramics system. It was noticeable that a large strain of around 0.4%, with a normalized strain value (d₃₃*) of 669 pm/V at the x = 0.02composition, by applying an electric field of 60 kV/cm at room temperature. The results of this study showed that a new BNT-BT-xBSn ceramics system is a very promising candidate for creating a significantly large strain response, which is sufficiently effective for actuator material applications.