IEEE

Maximum Likelihood Estimation Based Multi-Objective Evolutionary Algorithm for Parameter Optimization of SR-ADC

Abstract: Switched Reference Analog-to-Digital Converters (SR-ADCs) are widely used in Ultra-Wideband (UWB) Communication systems due to their high sampling efficiency and low hardware complexity.
science

Navigating high-dimensional processing parameters in organic photovoltaics via a multitier machine learning framework

Optimizing organic photovoltaic (OPV) performance requires navigating the high-dimensional, interdependent processing parameters governing bulk heterojunction morphology. To address this, we have ...
Frontiers

Study on robotic projectile launching based on multi-factor analysis and parameter optimization

The precision of projectile launching mechanisms, which utilize counter-rotating friction wheels, is critical for system effec-tiveness. This study introduces a hybrid approach combining multi-physics ...
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 ...
IEEE

Two-Stage Genetic Algorithm Offline Parameter Optimization of Adaptive Extended Kalman Filter for Robust Battery State-Of-Charge Estimation

Abstract: Accurately estimating battery state of charge (SOC) in electric vehicle applications (EVs) is crucial to ensure a safe and reliable vehicle operation. However, robust SOC estimation under ...