  Many real systems possess accelerating statistics where the total number of
edges grows faster than the network size. In this paper, we propose a simple
weighted network model with accelerating growth. We derive analytical
expressions for the evolutions and distributions for strength, degree, and
weight, which are relevant to accelerating growth. We also find that
accelerating growth determines the clustering coefficient of the networks.
Interestingly, the distributions for strength, degree, and weight display a
transition from scale-free to exponential form when the parameter with respect
to accelerating growth increases from a small to large value. All the
theoretical predictions are successfully contrasted with extensive numerical
simulations.
