论文部分内容阅读
文章针对Waxman模型提出了两种使用方便、平均点度精确的网络模型:PD1和PD2。并对几种主要模型通过实验进行了对比。结果表明,新方法产生的随机网络几乎在任何尺寸下都很接近实际的网络。同时,文中方法可使网络节点的平均点度非常精确,几乎等于预设的度。
The article proposes two kinds of network models that are easy to use and have an accurate average dot degree for the Waxman model: PD1 and PD2. Several main models are compared through experiments. The results show that the stochastic network generated by the new method is close to the actual network at almost any size. At the same time, the method in this paper can make the average degree of network nodes very accurate, almost equal to the preset degree.