Weighted Network scrambling algorithm

There are strong and weak links between individuals in social networks, the function and function of different connections are different, and there are uneven fluxes in each path in the metabolic network, and the interaction intensity of different species in the food chain network is different.

Compared with the unauthorized network, weighted network increases the weight of this important attribute, which provides a more detailed description of the relationships and interactions among nodes in the network, and is an important branch of complex network system.

Complex networks should not only analyze the topological properties of the network, but also analyze the heterogeneity of the edge strength. The topological correlation of weights plays an important role in the optimization of resource allocation in complex systems, and it is of great significance to study the network weight topological correlation. In this paper, we expound the concrete implementation of constructing weighted network 0 model scrambling algorithm from three aspects of weight, topological structure and random scrambling.

Weighted scrambling algorithm

Equal weight scrambling algorithm

Random Fault-Edge re-connection scrambling algorithm

Weighted Network scrambling algorithm