<正>以Marquardt非线性模型参数辨识为基础,以山本式二元立木动态材积模型为例,阐述了非线性参数估计的最小二乘原理,分析了估计方法的误差,采用二次项函数逼近的二次算法提高了材积模型的估计精度。以广东森林资源调查的样本资料,对提出的方法进行了验证与应用,结果表明改进的方法比原有的方法精度提高了一个数量级。

Forestry surveying and estimation are one of the most important business for forestry management.Tree volume measurement used table is one of the most important method in the forestry property evaluation.A better algorithm is the key for estimative precision of model.This paper,based on parametric identification of Marquardt nonlinear model,takes an example of Commonly Used Two-Way Tree Volume Model,elucidates the least-squares minimization of nonlinear parametric estimation and analyzes error of estimative algorithm.Quadric algorithm based on quadric function approximate is applied to improve estimative precision of Tree Volume Model.Forestry resources’s surveying sample data is tested for improved algorithm.The result shows that the improved algorithm can improve more 10 percent estimative precision than that of old algorithm.