• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. Forecasting a logistic service demand based on neural network
 
  • Details
  • Full
Options
2007
Conference Paper
Title

Forecasting a logistic service demand based on neural network

Abstract
Forecasting facilitates cutting down operational and management costs while ensuring service level for a logistics service provider. Our case study here is to investigate how to forecast logistic demand for a LTL carrier. First only time series forecasting is employed as no suitable explanatory indicators can be found for the regression approach. Among the times series forecasting methods, NN is adopted considering its feasibility and applicability. The simulation results verified its advantage over other two conventional time series approaches. The work done in the paper helps manager to select prediction method in practice.
Author(s)
Zhou, L.
Heimann, B.
Clausen, U.  
Fraunhofer-Institut für Materialfluss und Logistik IML  
Mainwork
ICSSSM '06, 2006 International Conference on Service Systems and Service Management. Proceedings. Vol.1  
Conference
International Conference on Service Systems and Service Management (ICSSSM) 2006  
DOI
10.1109/ICSSSM.2006.320518
Language
English
Fraunhofer-Institut für Materialfluss und Logistik IML  
Keyword(s)
  • neural network

  • logistic service demand

  • forecasting

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024