Tag: multi-objective optimization

Researchers combined tapered main channels with wavy sub-channels in a PEM fuel cell and used a physics-informed surrogate model with ...

Researchers combined an artificial neural network surrogate model with an enhanced NSGA-III algorithm to optimize a 20-tonne wave compensation Stewart ...

Researchers at NIT Durgapur compared NSGA-II, MOSA, and Bayesian optimization for designing tiny keyword spotting models, finding MOSA most reliable ...

A new study shows that calibrating watershed models with downscaled, bias-corrected satellite soil moisture data dramatically improves the representation of ...

A new Pareto-based particle swarm optimization framework jointly inverts magnetotelluric and Rayleigh wave data to map fractured, hydrothermally altered crustal ...

Researchers used explainable machine learning and multi-objective optimization to design a biodegradable Zn–Mg–Li alloy that overcomes the strength–ductility trade-off for ...

Researchers at Pacific Northwest National Laboratory have released pyMOODS, an open-source visual analytics framework that uses machine learning and rank-based ...

Researchers have developed a fuzzy multi-objective solid transportation model that simultaneously optimizes cost, transit time, and route security under uncertainty ...

A new hybrid AI framework combining deep convolutional networks with multi-objective evolutionary optimization achieves 98.5 percent accuracy in assessing vocational ...

A new study maps how chronic grid unreliability reshapes the optimal design of distributed solar and battery systems, finding that ...