Novel Intelligent Elevator Group Control Strategy Based on Rough Set
Effective mining the huge elevator data in elevator group control system is very important. In this paper, a novel intelligent elevator group control strategy based on rough set theory and fuzzy neural network called RS-FNN strategy is proposed. As a strong data fusion method, rough set theory can extract the most important system attributes. This proposed control method firstly reduce the main attributes in elevator group control system with discernibility matrix method in rough set thoery, and then build up a fuzzy neural network to control the elevator group. The simulation results show that this proposed novel elevator group control method can improve elevator system performance and adapt complicated traffic flow in variable elevator traffic flow conditions. This control method also can be applied to other similar fields.
Yuge Xu Fei Luo
College of Automation Science and Engineering, South China University of Technology, Guangzhou, 510640
国际会议
南宁
英文
2007-07-20（万方平台首次上网日期，不代表论文的发表时间）