Research of traffic pattern identification for elevator group control system based on GA-RBF neural network

被引：0

作者：

Wang Han ^{[1
]}

Yang Wei-guo ^{[1
]}

Wang Pai ^{[1
]}

机构：

[1] Northeastern Univ, Minist Educ, Coll Informat Sci & Engn, Key Lab Proc Ind Automat, Shenyang 110004, Peoples R China

来源：

PROCEEDINGS OF THE 2007 CHINESE CONTROL AND DECISION CONFERENCE | 2007年

关键词：

elevator group control; traffic flow pattern identification; RBF network; genetic algorithms;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A method of traffic pattern identification for elevator group control system based on genetic algorithms and RBF neural network is proposed. Elevator traffic flow is recognized by using RBF network. The centers and widths of RBF are specified by using k-means clustering algorithms. The network weight matrix is solved by applying leastsquare and the structure of the hidden layer of RBF network is optimized by using genetic algorithms. Simulation results show that the convergence speed of the proposed algorithm is faster and the precision of identification is higher.

引用

页码：307 / 310

页数：4