The Forecasting Approach of Short-term Traffic Volume based on Hierarchical Genetic Algorithm and ANFIS

摘要：

Adaptive Neural-Fuzzy Inference System(ANFIS) is a perfect method for nonlinear mapping problem which combines neural network and fuzzy inference system.But it only optimizes the internal parameters of the network,not the global structure parameters.In order to solve the problem,an approach to optimize the global structure parameters of ANFIS used by Hierarchical Genetic Algorithm (HGA) is presented.In HGA,every chromosome is coded by hierarchical binary.The genes in chromosome include FIS population,input variables and bit strings of membership function.The demonstration of short-term traffic volume forecasting proves that it can optimize global structure parameters and the results are satisfactory.

关键词： Hierarchical Genetic Algorithm ANFIS Short-term Traffic Volume Forecasting

作者: Xiao-li Zhang Hua-pu Lu

作者单位: Institute of Transportation Engineering,Tsinghua University,Beijing 100084,China

会议类型: 国际会议

会议名称: The 2008 International Conference on Business Intelligence and Financial Engineering(BIFE 2008)(商业智能和金融工程国际会议)

会议地点: 长沙

会议语种:英文

页码: 137-141

在线出版日期: 2008-10-28（万方平台首次上网日期，不代表论文的发表时间）