  We will introduce two evolving models that characterize weighted complex
networks. Though the microscopic dynamics are different, these models are found
to bear a similar mathematical framework, and hence exhibit some common
behaviors, for example, the power-law distributions and evolution of degree,
weight and strength. We also study the nontrivial clustering coefficient C and
tunable degree assortativity coefficient r, depending on specific parameters.
Most results are supported by present empirical evidences, and may provide us
with a better description of the hierarchies and organizational architecture of
weighted networks. Our models have been inspired by the weighted network model
proposed by Alain Barrat et al. (BBV for short), and can be considered as a
meaningful development of their original work.
