A scientific judgment on overload transport by subtractive fuzzy c-means algorithm & three-way decisions
Hao Wu, Qing-yun Luo, Si-yan Chen, Zhen-hua Zhang · 2017
In the developing world, overloading is very common due to the drive of interests. At present, overload transport has become a tough challenge to highway management in developing countries, and we cannot completely eradiate the phenomenon of overload transport. How to detect overloaded vehicles accurately in time in transportation inspection process has become an important research topic. This paper proposes a scientific judging method on overload transport, which is of high feasibility and scientificity. Firstly, the subtractive fuzzy c-means algorithm is applied to make a fuzzy cluster of all the freight drivers. Then, the crew is subdivided with the method of three-way decisions. Lastly, figure out significant aspects which are highly-relative with overload transport in terms of the result of cluster analysis. It has been proved that the method applied in this paper is more accurate and efficient than the traditional ones.