In order to schedule optimized dispatching for public bicycle network nodes, a feasible and efficient solution is proposed. In this paper, the usage records of public bicycles in a public city bicycle data management center are selected and studied by means of statistical physics. We firstly establish a wave mode group of stock fluctuation variation by closely tracking the fluctuation of boundary value, and construct a complex network of multi-time series combined the established wave mode group. Then the fluctuation, variation rule and influencing factors of the fluctuation mode group are analyzed by using complex network method. The analytical results show that the proposed inventory fluctuation complex network model provides effective guidance for real-time dynamic scheduling, and can provide helpful solutions for similar problems.
PENG Ya-li, ZENG Xin-yi, LÜ Ling, YANG Yu-xin, YIN Hong
. Prediction of Public Cycling Complex Network Scheduling Based on Wave Motion Modes[J]. Journal of Applied Sciences, 2018
, 36(4)
: 711
-722
.
DOI: 10.3969/j.issn.0255-8297.2018.04.014
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