Calibration Method Based on RBF Neural Networks for Soil Moisture Content Sensor

作     者：杨敬锋 李亭 卢启福 陈志民 YANG Jing-feng;LI Ting;LU Qi-fu;CHEN Zhi-min

作者机构：广东融讯信息科技有限公司广东广州510656 广东瑞图万方科技股份有限公司广东顺德528305 中山火炬职业技术学院广东中山528436 华南农业大学公共基础课实验教学中心广东广州510642 

出 版 物：《Agricultural Science & Technology》 (农业科学与技术（英文版）)

年 卷 期：2010年第11卷第2期

页      面：140-142页

学科分类：09[农学] 0903[农学-农业资源与环境] 090301[农学-土壤学] 

基　　金：Supported by Science and Technology Plan Project of Guangdong Province(2009B010900026,2009CD058,2009CD078,2009CD079,2009CD080) Special Funds for Support Program of Development of Modern Information Service Industry of Guangdong Province(06120840B0370124) Production and Research Cooperation Program of Shunde District(20090201024) Fund Project of South China Agricultural University(2007K017) 

主　　题：Calibration Model Soil Moisture Sensor Wireless Sensor Networks RBF Neural Networks 

摘      要：Temporal and spatial variation of soil moisture content is significant for crop growth,climate change and the other *** 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 *** results show that the calibration method is effective...