Research / Research News / A fusion-centric multi-stage ensemble approach for large-scale evaluation of renewable solar-powered water treatment system
Dr. Nahia Mourad, Assistant Professor & Prof. Bassam Abu-Hijleh, Professor in the Faculty of Engineering & IT, co-authored a paper titled, ‘A fusion-centric multi-stage ensemble approach for large-scale evaluation of renewable solar-powered water treatment system’ at the Applied Soft Computing.
This study proposes a fusion-based, multi-stage evaluation framework for renewable solar-powered water treatment systems to overcome the limitations of traditional assessment methods, such as dependence on single MCDM techniques, sensitivity to weighting and normalization, and reliance on expert judgment. The approach combines objective entropy weighting, multiple TOPSIS variants, HQP-based fusion, correlation filtering, and a Generative AI-assisted AHP to produce a robust consensus ranking.
The methodology was validated on 21 solar still configurations using six evaluation criteria. The results showed high consistency and reliability, demonstrating that the proposed framework effectively reduces bias, improves scalability, and enhances decision-making accuracy for large-scale system evaluations.
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