Gas Demand Forecasting Based on Artificial Neural Network PUBLIC ACCESS

[+] Author Affiliations
Kazuyoshi Miura

Teikoku Oil Company Ltd.

Ritsuo Sato

NKK Corporation

Paper No. IPC1998-2103, pp. 887-893; 7 pages
  • 1998 2nd International Pipeline Conference
  • Volume 2: Design and Construction; Pipeline Automation and Measurement; Environmental Issues; Rotating Equipment Technology
  • Calgary, Alberta, Canada, June 7–11, 1998
  • Conference Sponsors: Pipeline Division
  • ISBN: 978-0-7918-4023-8
  • Copyright © 1998 by ASME


Teikoku Oil Co. Ltd. (TOC) and NKK Corp. established a joint pilot project in 1994 in order to provide pipeline application and evaluation of NKK’s gas hydraulic simulation engine (GASTRAN) and to co-develop a Demand Forecasting Model (DFC). When the pilot project finished in March 1997, a commercial system, called Support Operation and Monitoring Application of Pipeline Simulator (SMAPS), was installed in TOC’s operation center.

The DFC, which is based on an artificial neural network architecture, has several advantages for sales forecasting especially as several dozen delivery points that have different sales patterns are connected to the pipeline network. The results from DFC can be easily used for scenarios in off-line simulation to predict future pipeline situations when it is attached to the SMAPS system. It automatically assists the pipeline operator by reducing his workload and evaluating operation plans.

Copyright © 1998 by ASME
This article is only available in the PDF format.



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In