Research on the combination forecasting method of logistics based on BP neural network

Wei Liu, Yajun Wang, Wenwei Gao, Peng Wang, Jianming Yang, Qiang Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper discussed the role and significance of Logistics forecast. Then classified the methods of Logistics forecast. Having given all the current forecasting methods a comparative analysis, this paper introduced a combination forecasting method based on BP neural network. Taking full advantage of the wide range of learning ability, adaptability of BP neural network, this paper integrated other methods and merited from them, then reached the goal of enhancing the precision and stability of forecasting results. Finally, using an example, it tested the new method and proved its feasibility.

Original languageEnglish
Title of host publicationProceedings of the 8th International Conference of Chinese Logistics and Transportation Professionals - Logistics
Subtitle of host publicationThe Emerging Frontiers of Transportation and Development in China
Pages4167-4173
Number of pages7
DOIs
StatePublished - 2008
Externally publishedYes
Event8th International Conference of Chinese Logistics and Transportation Professionals - Logistics: The Emerging Frontiers of Transportation and Development in China - Chengdu, China
Duration: 31 Jul 20083 Aug 2008

Publication series

NameProceedings of the 8th International Conference of Chinese Logistics and Transportation Professionals - Logistics: The Emerging Frontiers of Transportation and Development in China

Conference

Conference8th International Conference of Chinese Logistics and Transportation Professionals - Logistics: The Emerging Frontiers of Transportation and Development in China
Country/TerritoryChina
CityChengdu
Period31/07/083/08/08

Keywords

  • Forecast
  • Logistics
  • Neural network

Fingerprint

Dive into the research topics of 'Research on the combination forecasting method of logistics based on BP neural network'. Together they form a unique fingerprint.

Cite this