日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Automated experimentally validated antenna design framework using versatile parameterization scheme

采用通用参数化方案的自动化实验验证天线设计框架

Koziel, Slawomir; Pietrenko-Dabrowska, Anna; Szczepanski, Stanislaw

Globalized parameter tuning of microwave passives by dimensionality-reduced surrogates and multi-fidelity simulations

利用降维代理模型和多保真度仿真实现微波无源器件的全局参数调谐

Koziel, Slawomir; Pietrenko-Dabrowska, Anna

Fast globalized parameter tuning of antennas using simplex predictors, multilevel EM simulations and principal directions

利用单纯形预测器、多级电磁仿真和主方向法快速实现天线参数的全局调谐

Pietrenko-Dabrowska, Anna; Koziel, Slawomir

Rapid global antenna design by simplex regressors and multi-resolution simulations

基于单纯形回归器和多分辨率仿真的快速全局天线设计

Koziel, Slawomir; Pietrenko-Dabrowska, Anna; Szczepanski, Stanislaw; Leiffson, Leifur

Cost-efficient variable-fidelity machine learning for globalized optimization of microwave structures

用于微波结构全局优化的低成本可变保真度机器学习

Koziel, Slawomir; Pietrenko-Dabrowska, Anna; Szczepanski, Stanislaw

Surrogate modeling of passive microwave circuits using recurrent neural networks and domain confinement

利用循环神经网络和域约束对无源微波电路进行代理建模

Sahu, Kaustab C; Koziel, Slawomir; Pietrenko-Dabrowska, Anna

Machine learning for microwave optimization using simplex surrogates, dual-resolution computational models and local tuning with sparse sensitivity updates

利用单纯形代理模型、双分辨率计算模型和稀疏灵敏度更新的局部调谐进行微波优化的机器学习

Koziel, Slawomir; Pietrenko-Dabrowska, Anna

Variable-fidelity EM analysis and simplex-anchored regression surrogates for efficient global optimization of microwave passive circuits

用于微波无源电路高效全局优化的可变保真度电磁分析和单纯形锚定回归代理模型

Pietrenko-Dabrowska, Anna; Koziel, Slawomir

Accurate modeling of microwave structures in constrained domains using global sensitivity analysis and performance-based pre-screening

利用全局灵敏度分析和基于性能的预筛选方法,对受限域中的微波结构进行精确建模

Koziel, Slawomir; Pietrenko-Dabrowska, Anna

Efficient field correction of low-cost particulate matter sensors using machine learning, mixed multiplicative/additive scaling and extended calibration inputs

利用机器学习、混合乘法/加法缩放和扩展校准输入,对低成本颗粒物传感器进行高效的现场校正

Koziel, Slawomir; Pietrenko-Dabrowska, Anna; Wojcikowski, Marek; Pankiewicz, Bogdan