This study employs diverse machine learning models, including classic artificial neural network (ANN), hybrid ANN models, and the imperialist competitive algorithm and emotional artificial neural network (EANN), to predict crucial parameters such as fresh water production and vapor temperatures. Evaluation metrics reveal the integrated ANN-ICA model outperforms the classic ANN, achieving a remarkable 20% reduction in mean squared error (MSE). The emotional artificial neural network (EANN) demonstrates superior accuracy, attaining an impressive 99% coefficient of determination (R2) in predicting freshwater production and vapor temperatures. The comprehensive comparative analysis extends to environmental assessments, displaying the solar desalination system's compatibility with renewable energy sources. Results highlight the potential for the proposed system to conserve water resources and reduce environmental impact, with a substantial decrease in total dissolved solids (TDS) from over 6,000 ppm to below 50 ppm. The findings underscore the efficacy of machine learning models in optimizing solar-driven desalination systems, providing valuable insights into their capabilities for addressing water scarcity challenges and contributing to the global shift toward sustainable and environmentally friendly water production methods.
In this current investigation, the experimental performance of a solar still basin was significantly enhanced by incorporating snail shell biomaterials. The outcomes of the snail shell-augmented solar still basin (SSSS) are compared with those of a conventional solar still (CSS). The utilization of snail shells proved to facilitate the reduction of saline water and enhance its temperature, thereby improving the productivity of the SSSS. Cumulatively, the SSSS productivity was improved by 4.3% over CSS. Furthermore, the SSSS outperformed in energy and exergy efficiency of CSS by 4.5 and 3.5%, respectively. Economically, the cost per liter of distillate (CPL) for the CSS was 3.4% higher than SSSS. Moreover, the SSSS showed a shorter estimated payback period (PBP) of 141 days which was 6 days less than CSS. Considering the environmental impact, the observed CO2 emissions from the SSSS were approximately 14.6% higher than CSS over its 10-year lifespan. Notably, the SSSS exhibited a substantial increase in the estimated carbon credit earned (CCE) compared to the CSS. Ultimately, the research underscores the efficacy of incorporating snail shells into solar still basins as a commendable approach to organic waste management, offering economic benefits without compromising environmental considerations.