Title :
Research on the security of railway dangerous goods station based on rough ACO algorithm
Author_Institution :
Key Lab. of Numerical Simulation of Sichuan Province, Neijiang Normal Univ., Neijiang, China
Abstract :
By analyzing the impact factors of railway dangerous goods station, there are so many indexes of impact factors that not easy to grasp the key factors. We use the rough ant colony algorithm to attribute reduction for simplify the indexes in this paper. Then the attribute significance of rough set is applied to allocate weight coefficient for the reduced factor indexes with more objective way, which overcomes the subjective factor of the traditional method of determining the weight. That we can take effective measures focused on the important factors.
Keywords :
optimisation; railway safety; rough set theory; attribute reduction; impact factors; railway dangerous goods station security; reduced factor indexes; rough ACO algorithm; rough ant colony algorithm; rough set; Algorithm design and analysis; Ant colony optimization; Computer security; Data security; Educational institutions; Information security; Laboratories; Numerical simulation; Rail transportation; Railway safety; ACO algorithm; attribute reduction; rough set; weight;
Conference_Titel :
Computer Design and Applications (ICCDA), 2010 International Conference on
Conference_Location :
Qinhuangdao
Print_ISBN :
978-1-4244-7164-5
Electronic_ISBN :
978-1-4244-7164-5
DOI :
10.1109/ICCDA.2010.5541198
