Machine Learning Prediction of X-Band Microwave Absorption Using KNN Regression for Single-Slot Pyramidal Microwave Absorbers

DOI

10.2991/978-94-6239-745-3_22How to use a DOI?

Keywords

microwave absorber; X-band; k-nearest neighbour; machine learning; pyramidal absorber

Abstract

This paper presents a machine learning modelling approach for predicting microwave absorption performance of single-slot pyramidal microwave absorbers operating in the X band frequency range (8–12 GHz). The absorbers were fabricated using biomass derived carbon coating material as part of a sustainable microwave absorber design and configured with three slot sizes, namely small, medium, and big. Experimental absorption data were obtained from multiple frequency measurements and used as the dataset for modelling. Prior to modelling, the experimental data were preprocessed using interquartile range (IQR) outlier removal followed by Min Max normalization to ensure consistent scaling of the input and output variables. The modelling process was carried out using the k Nearest Neighbour (KNN) regression algorithm to predict the absorption performance based on normalized frequency and slot size. The dataset was divided into 70% training data and 30% testing data using the holdout method. Different values of k were tested to determine the optimal number of neighbours for the KNN model. The model performance was evaluated using coefficient of determination (R²) and root mean square error (RMSE). The results show that the proposed KNN model achieved high prediction accuracy with R² values greater than 0.97 and RMSE values below 0.05 for the X-band dataset. The comparison between slot sizes indicates that the absorption behaviour can be predicted consistently using the trained model. The study demonstrates that KNN-based machine learning modelling is suitable for predicting microwave absorption performance of sustainable pyramidal microwave absorbers using experimental data and can reduce the need for extensive measurements in absorber design.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits any noncommercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if you modified the licensed material. You do not have permission under this license to share adapted material derived from this chapter or parts of it.

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TY  - CONF
AU  - Yaakub Omar
AU  - Ilya Ismail
AU  - Nur Athirah Syafiqah Noramli
AU  - Nurlaila Ismail
AU  - Hasnain Abdullah
AU  - Mohd Nasir Taib
PY  - 2026
DA  - 2026/08/24
TI  - Machine Learning Prediction of X-Band Microwave Absorption Using KNN Regression for Single-Slot Pyramidal Microwave Absorbers
BT  - Proceedings of the International Conference on Research, Innovation, Sustainability, and Educations (IRISECON 2026)
PB  - Atlantis Press
SP  - 335
EP  - 349
SN  - 3091-4442
UR  - https://doi.org/10.2991/978-94-6239-745-3_22
DO  - 10.2991/978-94-6239-745-3_22
ID  - Omar2026
ER  -