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31. Retraction notice to “Utilization of machine learning and neural networks to optimize the enclosure angle, magnetic field, and radiation parameter for mixed convection of hybrid nanofluid flow next to assess environmental impact” [Engineering Analysis with Boundary Elements 146 (2023) 252-262]

39. Comparison analysis of hydrogen addition into both anode and afterburner of fuel cell incorporated with hybrid renewable energy driven SOFC: An application of techno-environmental horizon and multi-objective optimization

45. Utilization of machine learning and neural networks to optimize the enclosure angle, magnetic field, and radiation parameter for mixed convection of hybrid nanofluid flow next to assess environmental impact

46. Deep learning optimization and techno-environmental analysis of a solar-driven multigeneration system for producing sustainable hydrogen and electricity: A case study of San Francisco

50. Enhanced hydrogen generation in a combined hybrid cycle using aluminum and cooper oxide nanomaterial based on biomass and vanadium chloride cycle: Optimization based on deep learning techniques and Environmental appraisal

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