CST_Simulation _Antenna_Design_Dataset

This dataset contains 1,000 unique antenna configurations generated through parametric electromagnetic (EM) simulations using CST Studio Suite 2025. The dataset is specifically designed to support the training and validation of machine learning (ML) surrogate models for the automated design and optimization of dual-band wearable antennas. It captures the non-linear relationship between physical antenna geometry and electromagnetic performance metrics, enabling rapid, AI-driven antenna synthesis without the need for repetitive, time-intensive full-wave simulations.本数据集包含1000种独特的天线构型，均通过CST Studio Suite 2025开展的参数化电磁（Electromagnetic, EM）仿真生成。本数据集专为支持双频段可穿戴天线自动化设计与优化的机器学习（Machine Learning, ML）代理模型的训练与验证工作而构建。该数据集捕捉了天线物理几何参数与电磁性能指标之间的非线性关系，可实现人工智能驱动的快速天线综合，无需进行重复且耗时的全波仿真。