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作 者:林剑辉[1] 孙宇瑞[1] 曾庆猛[1] P. Schulze Lammers
机构地区:[1]中国农业大学信息与电气工程学院,北京100083 [2]德国波恩大学农业工程研究所,德国波恩53115
出 处:《应用基础与工程科学学报》2008年第6期779-786,共8页Journal of Basic Science and Engineering
基 金:国家自然科学基金(30800665);国家“863”计划(2006AA10Z205);中德科学中心基金(GZ494)
摘 要:应用一种先进的双变量(土壤圆锥指数与水分)传感器复合测量系统,基于前人提出的土壤圆锥指数、水分与容重的4种半经验模型(Ayers,Upadhyaya,Busscher与Hernanz模型),以相关系数R2与统计残差作为检验指标,根据各模型的结构特点,结合两种质地土壤(粘土与粉质壤土),针对容重预测精度与可应用性进行了深入试验研究.结果表明,Ayers和Upadhyaya模型虽然预测精度较高,但与土壤容重的解析关系为隐函数,在线辨识计算工作量只能取决迭代过程的收敛性,因而在实际应用上受到一定程度的限制.相比之下Busscher与Hernanz模型计算土壤容重方便快捷,但预测精度较低.Using an advanced dual-sensor technique for the simultaneous measurement of soil cone index and volumetric water content, four proposed semi-empirical models (Ayers-, Upadhyaya-, Busscher- and Hemanz-model ) have been validated with R2( coefficient of determination) and RMSE (Root Means Square Error). For this objective, two types of soil samples, clay and silt-loam, were used in the experiment. Moreover, soil bulk density acted as a predicted parameter for evaluating the performance of each model. The experimental and computational results demonstrate that both Ayers- and Upadhyaya-model can achieved better predication for the system identification but they are unable to be an explicit function among volumetric water content, cone index and bulk density. Therefore, the applicability of both models in the field depends on their convergence of the iterative process. Alternatively, Busscher- and Hernanz-model have no any restriction during on-line computation, although their predicting performance seems relatively poor.
分 类 号:S146[农业科学—肥料学] S24[农业科学—农业基础科学]
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