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- W4319978022 abstract "The forward problem plays an important role in microwave inversion, but numerical (3-D) forward modeling methods are usually computationally expensive, limiting the inversion efficiency. This paper provides a simplified method based on the Back Propagation (BP) neural network for 3-D forward modeling. The simplification is realized based on a 2-D simulation and BP neural network hybrid procedure. The field data at receivers in 3-D problems. 2-D and 3-D simulations are made to generate synthetic data. A BP neural network mapping 2-D data to 3-D data is established, trained, and tested with the generated data. The average prediction accuracy is less than 2%. The average time cost is primarily reduced to 1% of 3-D simulation. This method can be applied to 3-D microwave imaging applications for fast inversion." @default.
- W4319978022 created "2023-02-11" @default.
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- W4319978022 date "2022-08-01" @default.
- W4319978022 modified "2023-09-23" @default.
- W4319978022 title "A Feasibility of 3-D Microwave Forward Modelling Simplification based on Back Propagation Neural Network" @default.
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- W4319978022 doi "https://doi.org/10.1109/cipae55637.2022.00045" @default.
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