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→Barabási–Albert (BA) 优先链接模型
The [[Barabási–Albert model]] is a random network model used to demonstrate a preferential attachment or a "rich-get-richer" effect. In this model, an edge is most likely to attach to nodes with higher degrees.The network begins with an initial network of ''m''<sub>0</sub> nodes. ''m''<sub>0</sub> ≥ 2 and the degree of each node in the initial network should be at least 1, otherwise it will always remain disconnected from the rest of the network.
The [[Barabási–Albert model]] is a random network model used to demonstrate a preferential attachment or a "rich-get-richer" effect. In this model, an edge is most likely to attach to nodes with higher degrees.The network begins with an initial network of ''m''<sub>0</sub> nodes. ''m''<sub>0</sub> ≥ 2 and the degree of each node in the initial network should be at least 1, otherwise it will always remain disconnected from the rest of the network.
However, for <math>m=1</math> it describes the winner takes it all mechanism as we find that almost <math>99\%</math> of the total nodes have degree one and one is super-rich in degree. As <math>m</math> value increases the disparity between the super rich and poor decreases and as <math>m>14</math> we find a transition from rich get super richer to rich get richer mechanism.
However, for <math>m=1</math> it describes the winner takes it all mechanism as we find that almost <math>99\%</math> of the total nodes have degree one and one is super-rich in degree. As <math>m</math> value increases the disparity between the super rich and poor decreases and as <math>m>14</math> we find a transition from rich get super richer to rich get richer mechanism.
=== Barabási–Albert (BA) 优先链接模型 ===
BA模型是一个随机网络模型，用于说明偏好依附效应（优先链接）preferential attachment或“富人越富”效应。 在这个模型中，边最有可能附着在度数较高的节点上。 这个网络从一个 m0节点的初始网络开始。 M0≥2，初始网络中每个节点的度至少为1，否则它将始终与网络的其余部分断开。
=== Fitness model ===
=== Fitness model ===