Prediction models of the number of end-of-life vehicles in China

Guangdong Tian, Mengchu Zhou, Jiangwei Chu, Bing Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Prediction along with future trend analysis of the volume of end-of-life vehicles (ELVs) has a great impact on the execution of regulations and formulation of policies in China. To deal with such issues, this work investigates the historical data of their major influence factors including production volume, sale volume, vehicle count, turnover of highway freight, passenger turnover, GDP and income of per urban resident. Moreover, based on obtained main factors and historical data of ELV volume in China, its prediction models are established by multiple linear regressions (MLR), neural networks (NN) and optimized NN based on genetic algorithm (GA-NN) methods. In addition, a numerical example is given to illustrate the proposed models and the effectiveness of the proposed methods.

Original languageEnglish (US)
Title of host publicationProceedings of the 2013 International Conference on Advanced Mechatronic Systems, ICAMechS 2013
PublisherIEEE Computer Society
Pages357-362
Number of pages6
ISBN (Print)9781479925193
DOIs
StatePublished - 2013
Event2013 International Conference on Advanced Mechatronic Systems, ICAMechS 2013 - Luoyang, China
Duration: Sep 25 2013Sep 27 2013

Publication series

NameInternational Conference on Advanced Mechatronic Systems, ICAMechS
ISSN (Print)2325-0682
ISSN (Electronic)2325-0690

Other

Other2013 International Conference on Advanced Mechatronic Systems, ICAMechS 2013
Country/TerritoryChina
CityLuoyang
Period9/25/139/27/13

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Mechanical Engineering

Keywords

  • China
  • End-of-life vehicles
  • Modeling and simulation
  • Prediction

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