Tag: multi-objective optimization

Researchers at Fujian Normal University have developed a color image watermarking method in the discrete quaternionic quadratic phase Fourier transform ...

Researchers have combined conditional diffusion models with graph neural networks to generate coordinated energy schedules for building clusters, achieving a ...

A three-year field study in the North China Plain identifies optimal irrigation and nitrogen ranges that simultaneously raise grain yield, ...

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 ...