Dual-Band Stub-Loaded Monopole Antenna Optimization Data

A 3.7 KB dataset containing simulation results for a compact dual-band antenna optimized for WLAN (2.4 GHz) and 5–6 GHz applications. The data was generated by Jun-Jiat Tiang using 210 HFSS-simulated samples to train an artificial neural network surrogate model, achieving R² > 0.99 for training and validation. It was last updated on June 1, 2026.

Use Cases

• Training surrogate models for antenna performance prediction based on the described ANN with R² > 0.99
• Comparing bandwidth enhancement techniques for stub-loaded monopoles based on the reported −10 dB impedance bandwidths
• Optimizing dual-band antenna designs using a weighted figure-of-merit (FOM) based on the described methodology with tunable band prioritization
• Benchmarking simulation efficiency by comparing ANN prediction times (seconds) against full electromagnetic simulations (minutes)

Strengths

• Includes performance metrics for a dual-band antenna with −10 dB impedance bandwidths of 1.7–2.7 GHz (45.5%) and 5.1–5.9 GHz (14.5%)
• Based on a surrogate model trained on 210 simulated samples, achieving high predictive accuracy with R² > 0.99 for both training and validation
• Describes a clear optimization methodology using a weighted FOM (with weights w₂ = w₄ = 1.5) to prioritize upper-band performance

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• The dataset is very small (3.7 KB), indicating limited scope, likely containing summary results or parameters rather than raw simulation data

Provenance

Source

Jun-Jiat Tiang via figshare

Collection Method

Data generated from 210 HFSS electromagnetic simulations, used to train an artificial neural network surrogate model.

Freshness

Last updated 2026-06-01 05:35:57