Calibration method based on RBF neural networks for soil moisture content sensor | 基于RBF神经网络的土壤含水量传感器标定方法
2010
Yang Jingfeng, Guangdong Rocent Information Technology Co.Ltd, Guangzhou (China) | Yang Jingfeng, Zhongshan Torch Polytechnic, Zhongshan (China) | Yang Jingfeng, Guangdong Rocent Information Technology Co.Ltd, Guangzhou (China)
Temporal and spatial variation of soil moisture content is significant for crop growth, climate change and the other fields. In order to overcome shortage of non-linear output voltage of TDR3 soil moisture content sensor and increase soil moisture content data collection and computational efficiency, this paper presents a RBF neural network calibration method of soil moisture content based on TDR3 soil moisture sensor and wireless sensor networks. Experiment results show that the calibration method is effective, simple and practical, and provides an effective method for real-time monitoring of soil moisture content.
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