Abstract
This paper proposed a new method to classify soil pH based on long short-term memory (LSTM) via ultra-wideband (UWB) radar echoes. The main contribution of this paper is to provide a solution by incorporating the LSTM into the field experiment related to UWB based on soil pH echoes. Five types of UWB soil echoes with different pH values are collected and investigated using LSTM approach. Finally, the analysis of results shows that LSTM method presents a good classification performance with a short execution time and the data features do not need to be extracted manually. The high accuracy rate also shows that LSTM method is beneficial to the study of other soil parameters.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China (61671138, 61731006), and was partly supported by the 111 Project No. B17008.
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Wang, T., Zhu, F., Liang, J. (2020). Soil pH Classification Based on LSTM via UWB Radar Echoes. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-13-6504-1_92
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DOI: https://doi.org/10.1007/978-981-13-6504-1_92
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