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Hybrid modeling strategy based on deep learning surrogate models enables accurate multi-objective optimization of iso-octanol oxidation

Researchers have developed a hybrid surrogate model for iso-octanol oxidation to iso-octanal that integrates data-driven ...
IEEE

A Multi-Objective Optimization Method for UI Interfaces Integrating NSGA-II and Simulated Annealing

Abstract: Traditional user interface layout design heavily relies on designers' subjective judgment and lacks effective quantitative assessment methods. This study aims to overcome this shortcoming.
Scientific Research Publishing

Comparative Performance of Propensity Score Methods for Clinical Multi-Group Data: Balancing Confounders and Estimating Treatment Effects ()

1 Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China. 2 School of International Education, Southern Medical University, Guangzhou, China. 3 Guangdong ...
Frontiers

CLMOAS: collaborative large-scale multi-objective optimization algorithms with adaptive strategies

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...
Frontiers

Robust multi-objective optimization framework for performance-based seismic design of steel frame with energy dissipation system

Modern seismic codes ensure life safety, but code-compliant buildings can still suffer significant economic losses from earthquake-induced damage, even during moderate events. Performance-Based ...
IEEE

Multi-Objective Optimization Design of an Axial-Flux Permanent Magnet Flywheel Machine Using Fuzzy Inference Taguchi Method

Abstract: The Taguchi method is an efficient method for machine optimization design. Unfortunately, the conventional Taguchi method is hard to obtain a complete set of nondominated solutions due to ...