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Percolation is related to the robustness of the graph (called also network). Given a random graph of <math>n</math> nodes and an average degree <math>\langle k\rangle</math>. Next we remove randomly a fraction <math>1-p</math> of nodes and leave only a fraction <math>p</math>. There exists a critical percolation threshold <math>p_c=\tfrac{1}{\langle k\rangle}</math> below which the network becomes fragmented while above <math>p_c</math> a giant connected component exists.
Percolation is related to the robustness of the graph (called also network). Given a random graph of <math>n</math> nodes and an average degree <math>\langle k\rangle</math>. Next we remove randomly a fraction <math>1-p</math> of nodes and leave only a fraction <math>p</math>. There exists a critical percolation threshold <math>p_c=\tfrac{1}{\langle k\rangle}</math> below which the network becomes fragmented while above <math>p_c</math> a giant connected component exists.
'''<font color="#FF8000">渗流 Percolation </font>''' 与图形(也称为网络)的'''<font color="#FF8000">健壮性 Robustness </font>'''有关。给定一个随机图形，其中的节点是 <math>n</math> 和一个平均度 <math>\langle k\rangle</math> 。接下来我们随机移除一部分节点，只留下一部分节点。存在一个临界渗透阈值，低于这个临界渗透阈值，网络变得支离破碎，而高于临界渗透阈值的网络则存在一个巨大的'''<font color="#FF800">连接元件 Connected Component </font>'''(图论)。
'''<font color="#FF8000">渗流 Percolation </font>''' 与图形(也称为网络)的'''<font color="#FF8000">健壮性 Robustness </font>'''有关。给定一个随机图形，其中的节点是 <math>n</math> 和一个平均度 <math>\langle k\rangle</math> 。接下来我们随机移除一部分概率为<math>1-p</math>的节点，只留下一部分概率为<math>p</math>的节点。存在一个临界渗透阈值<math>p_c=\tfrac{1}{\langle k\rangle}</math>，当低于这个临界渗透阈值，网络变得支离破碎，而高于临界渗透阈值<math>p_c</math>的网络则存在一个巨大的'''<font color="#FF800">连接元件 Connected Component </font>'''(图论)。
<ref>{{cite book |title= Complex Networks: Structure, Robustness and Function |authors= Reuven Cohen and [[Shlomo Havlin]] |year= 2010 |url= http://havlin.biu.ac.il/Shlomo%20Havlin%20books_com_net.php |publisher= Cambridge University Press}}</ref><ref name ="On Random Graphs" />
<ref>{{cite book |title= Complex Networks: Structure, Robustness and Function |authors= Reuven Cohen and [[Shlomo Havlin]] |year= 2010 |url= http://havlin.biu.ac.il/Shlomo%20Havlin%20books_com_net.php |publisher= Cambridge University Press}}</ref><ref name ="On Random Graphs" />