作者
Sedat Metlek, Kiyas Kayaalp, Ibrahim Bahadir Basyigit, Abdullah Genc, Habib Dogan
发表日期
2021/1
期刊
International Journal of RF and Microwave Computer‐Aided Engineering
卷号
31
期号
1
页码范围
e22496
出版商
John Wiley & Sons, Inc.
简介
In this paper, dielectric properties of citrus leaves are predicted with long short‐term memory (LSTM) which is one of the well‐known deep neural network (DNN) models and real‐time measurements for any moisture content (MC) values in the range of 4.90 to 7.05 GHz at a fixed temperature of 24°C for microwave applications, as a novelty. Firstly, S‐parameters of samples are measured with WR‐159 waveguide and Waveguide Transmission Line Method. In addition, the MCs of samples depending on their weights are calculated. Thus, the dataset depending on various MC and frequency is obtained with the measurement results to both training and testing the DNN model. Secondly, a total of 4000 datasets are obtained, 80% of which is used for training, and 20% for testing. The proposed DNN model consists of four inputs (f, MC, S11, and S21) and two outputs (ε′ and ε″). Finally, the dielectric parameters for …
引用总数
20212022202320246896
学术搜索中的文章
S Metlek, K Kayaalp, IB Basyigit, A Genc, H Dogan - International Journal of RF and Microwave Computer …, 2021