We present and investigate a general nonlinear growth network model which incorporates accelerated growth of nodes and edges.
本文提出了一个非线性扩张的复杂网络模型，在这个模型中，同时考虑了节点和边的非线性增长。
Recently, researchers have reported a lot of imitating real network evoluting growth model, in which a part of them are based on network aggregation growth.
最近研究人员提出了很多模拟真实网络演化生长的理论模型，其中一部分模型是从网络聚集生长出发的。
At last, this paper will also apply the stand density model established with artificial neural network in asset assessment of forest resources and the estimation of growth and harvest.
最后，本文还将把人工神经网络建立的林分密度模型用于森林资源资产评估，进行生长收获的预估。
Started from exponential growth of scale-free network, the analytic and simulated results of the modified BA model are presented in the paper.
从无标度网络指数式演化的角度，给出了BA修改模型的解析结果和数值模拟。
Based on a detailed research on these two ways, the paper chooses triangle network growth algorithm to build TIN model and utilizes Grid growth triangle network model to build 3d strata.
本文详尽地研究这两种构模方法的基础上，采用三角网生长算法生成了地质层面tin，同时利用格网数据生成三角网法实现了地质层面三维可视化。
Based on a detailed research on these two ways, the paper chooses triangle network growth algorithm to build TIN model and utilizes Grid growth triangle network model to build 3d strata.
本文详尽地研究这两种构模方法的基础上，采用三角网生长算法生成了地质层面tin，同时利用格网数据生成三角网法实现了地质层面三维可视化。
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