Elevator Safety Evaluation Based on AHP and PSO-BP Neural Network
WAN Zhou
TANG Chao
XU Youcai
Abstract：In assessing the degree of elerator security risk ,for the weakness of BP neural network with slow conver‐gence speed and falling into local optimum easily ,a method based on Analytic Hierarchy Process(AHP) and Particle Swarm Optimization(PSO‐BP) is proposed to evaluate the safety of elevator .First of all ,the elevator evaluation system can be built by AHP to determine the subsystem and the weight in the elevator system security evaluation system .Then ,according to safety norms ,combined with practical experience the risk value of every index can be obtained .PSO optimizes the weights and thresholds of the A linear model of BP neural network .Eleven factors in the elevator system whose weight is heavy se‐lected as the input of PSO‐BP .Finally ,the composite scores which represent the security situation of the elevator system are gotten .According to the score ,the safety assessment level and the conclusion are gotten .Through comparing PSO‐BP with BP ,the result shows that PSO‐BP can improve the precise by 10% than BP ,and PSO‐BP overcomes the shortcomings of BP neural network .
Keywords：elevator systemsafety assessmentanalytic hierarchy processparticle swarm optimization algorithmBP neural network
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 1561-1565,1598 )