A hybrid machine learning and metaheuristic framework optimizes sludge, fly ash, slag, and gypsum mixtures to improve compressive strength. The approach enables sustainable sludge reuse, reduces waste ...
ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...
Abstract: Metaheuristic algorithms are implemented to solve optimization problems and have recently received significant research attention. Metaheuristic algorithms rely primarily on two properties, ...
As carriers of green energy, proton exchange membrane fuel cells (PEMFCs) and photovoltaic (PV) cells are complex and nonlinear multivariate systems. For simulation analysis, optimization control, ...
Abstract: A variable reduction strategy (VRS) drives evolutionary algorithms (EAs) to evolve more effectively by simplifying optimization problems. To represent a decision space with the smallest set ...
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