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A Modified Efficient KNN Method for Antenna Optimization and Design

https://doi.org/10.1109/tap.2020.3001743

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inferred← citeshttps://doi.org/10.2528/pierm21122802openalex-snapshot

ULTRA-WIDEBAND CPW FED BAND-NOTCHED MONOPOLE ANTENNA OPTIMIZATION USING MACHINE LEARNING

inferred← citeshttps://doi.org/10.2528/pierm22061804openalex-snapshot

SBD SYNTHESIS OF DUAL-BAND PERTURBED MINKOWSKI MONOPOLE FRACTAL ANTENNAS

inferred← citeshttps://doi.org/10.2528/pierm23062505openalex-snapshot

Employing Machine Learning Models to Predict Return Loss Precisely in 5G Antenna

inferred← citeshttps://doi.org/10.28991/hef-2022-03-04-01openalex-snapshot

Tesla Stock Close Price Prediction Using KNNR, DTR, SVR, and RFR

inferred← citeshttps://doi.org/10.32604/cmc.2022.027653openalex-snapshot

Optimized Two-Level Ensemble Model for Predicting the Parameters of Metamaterial Antenna

inferred← citeshttps://doi.org/10.32604/cmc.2022.028550openalex-snapshot

Improved Prediction of Metamaterial Antenna Bandwidth Using Adaptive Optimization of LSTM

inferred← citeshttps://doi.org/10.3390/app11041627openalex-snapshot

Machine Learning for Design Optimization of Electromagnetic Devices: Recent Developments and Future Directions

inferred← citeshttps://doi.org/10.3390/app112210829openalex-snapshot

Machine Learning Technique to Improve an Impedance Matching Characteristic of a Bent Monopole Antenna

inferred← citeshttps://doi.org/10.3390/electronics10222752openalex-snapshot

Application of Machine Learning in Electromagnetics: Mini-Review

inferred← citeshttps://doi.org/10.3390/electronics12061429openalex-snapshot

KNN-Based Consensus Algorithm for Better Service Level Agreement in Blockchain as a Service (BaaS) Systems

inferred← citeshttps://doi.org/10.3390/electronics12163462openalex-snapshot

On Unsupervised Artificial Intelligence-Assisted Design of Antennas for High-Performance Planar Devices

inferred← citeshttps://doi.org/10.3390/electronics12204195openalex-snapshot

Intelligent Design Prediction of a Circular Polarized Antenna for CubeSat Application Using Machine Learning Algorithms

inferred← citeshttps://doi.org/10.3390/electronics9111750openalex-snapshot

Electromagnetic Micro-Structure Non-Destructive Testing: Sparsity-Constrained and Combined Convolutional Recurrent Neural Network Methods

inferred← citeshttps://doi.org/10.36227/techrxiv.171742511.11489750/v1openalex-snapshot

Rapid Multi-Objective Inverse Design of Antenna Via Deep Neural Network Surrogate-Driven Evolutionary Optimization

inferred← citeshttps://doi.org/10.36227/techrxiv.19164623openalex-snapshot

Multibranch Machine Learning-Assisted Optimization and Its Application to Antenna Design

inferred← citeshttps://doi.org/10.36227/techrxiv.19164623.v1openalex-snapshot

Multibranch Machine Learning-Assisted Optimization and Its Application to Antenna Design

inferred← citeshttps://doi.org/10.4018/979-8-3693-2659-6.ch004openalex-snapshot

An Overview of Applications of Machine Learning Techniques in Antenna Design and Optimization

inferred← citeshttps://doi.org/10.4018/979-8-3693-2659-6.ch005openalex-snapshot

Revolutionizing Antenna Design

inferred← citeshttps://doi.org/10.70675/457bc189zbc24z462ez9629z37ba40d65dd1openalex-snapshot

Imaging and diagnostic of sub-wavelength micro-structures, from closed-form algorithms to deep learning

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