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In developing countries, evaluating irrigation water quality using conventional methods can be costly and time-consuming. To overcome these challenges, this study explores the potential of utilizing physical parameters and artificial intelligence (AI) models for predicting and evaluating the quality indicators of irrigation water in aquifer systems. To achieve this goal, novel hybrid methods, namely the Whale Optimization Algorithm (WOA) and Wind-Driven Optimization (WDO), are employed in conjunction with Artificial Neural Network (ANN) models. The specific objective of this study is to forecast the Sodium Adsorption Ratio (SAR) by considering independent variables such as Na+, Mg2+, Ca2+, Na percent, K+, SO42−, Cl−, pH, and HCO3−. A dataset of 540 samples from the Shiraz plain, collected over a statistical period of 16 years (2002–2018), is used to estimate the groundwater quality variables. A pre-processing technique is applied in the AI approach to enhance the model's efficiency. The results indicate that the WDO-ANN model exhibits higher accuracy (R2 = 0.9983 and RMSE = 0.10618) than the WOA-ANN model (R2 = 0.9957 and RMSE = 0.16957). The optimization of computational parameters and comparison of AI model structures demonstrate that the WDO-ANN model outperforms the WOA-ANN model in predictive ability. In general, using AI models as a tool for low-cost and timely prediction of underground water quality using physical parameters as input variables has a high potential. [ABSTRACT FROM AUTHOR]

To fabricate stable neat FAPbI3 perovskite with a pure α‐phase (pure α‐FAPbI3) is important in the field of photovoltaic commercialization because of its better bandgap than its alloying counterpart with cesium (Cs) or methylammonium (MA) cations. In this study, the first vapor deposited pure α‐FAPbI3 thin film solar cell with a power conversion efficiency (PCE) over 20% is achieved by regulating the phase transition process. It is found that under high humidity conditions, a fast phase transition between high‐purity α‐ and δ‐phase FAPbI3 can be realized. Moreover, theoretical calculations interestingly reveal a phase transition shortcut induced by the abnormal volume contraction that is ascribed to the formation of double hydrogen bonds at a certain H2O concentration. Therefore, a high‐humidity post‐treatment strategy is proposed to fabricate α‐FAPbI3 solar cells with a champion PCE of 20.19% (0.1 cm2) and 18.91% (1 cm2), which is currently the highest recorded value in vapor deposited pure α‐FAPbI3 perovskite solar cells. This study helps to redefine the effect of a water molecule on FAPbI3 solar cells. In addition, the demonstrated scaling‐up possibility provides another perspective for fabricating uniform high‐performance pure α‐FAPbI3 perovskite solar cells. [ABSTRACT FROM AUTHOR]