NISCAIR Online Periodicals Repository

Research Journals >
Journal of Scientific and Industrial Research (JSIR) >
JSIR Vol.69 [2010] >
JSIR Vol.69(03) [March 2010] >

Title: An ANFIS algorithm for improved forecasting of oil consumption: a case study of USA, Russia, India and Brazil
Authors: Azadeh, Ali
Saberi, Morteza
Ghorbani, Sara
Keywords: Adaptive network based fuzzy inference system (ANFIS)
Mean absolute percentage error (MAPE)
Oil consumption estimation
Issue Date: Mar-2010
Publisher: CSIR
Abstract:  This paper proposed an adaptive network-based fuzzy inference system (ANFIS) algorithm for oil consumption forecasting based on monthly oil consumption (January 2001 - September 2006) in USA, Russia, India and Brazil. Using mean absolute percentage error (MAPE), efficiency of different ANFIS models was examined. Proposed algorithm used Autocorrelation Function (ACF) to define input variables irrespective of trial and error method (TEM). Algorithm for calculating ANFIS performance is based on its closed and open simulation abilities.
Page(s): 194-203
ISSN: 0975-1084 (Online); 0022-4456 (Print)
Source:JSIR Vol.69(03) [March 2010]

Files in This Item:

File Description SizeFormat
JSIR 69(3) 194-203.pdf125.18 kBAdobe PDFView/Open
 Current Page Visits: 1341 
Recommend this item


Online Submission of Articles |  NISCAIR Website |  National Knowledge Resources Consortium |  Contact us |  Feedback

Disclaimer: NISCAIR assumes no responsibility for the statements and opinions advanced by contributors. The editorial staff in its work of examining papers received for publication is helped, in an honorary capacity, by many distinguished engineers and scientists.

CC License Except where otherwise noted, the Articles on this site are licensed under Creative Commons License: CC Attribution-Noncommercial-No Derivative Works 2.5 India

Copyright © 2015 The Council of Scientific and Industrial Research, New Delhi. All rights reserved.

Powered by DSpace Copyright © 2002-2007 MIT and Hewlett-Packard | Compliant to OAI-PMH V 2.0

Home Page Total Visits: 167873 since 01-Sep-2015  Last updated on 29-Jun-2016Webmaster: