Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/7378
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.
Description: 194-203
URI: http://hdl.handle.net/123456789/7378
ISSN: 0975-1084 (Online); 0022-4456 (Print)
Appears in Collections:JSIR Vol.69(03) [March 2010]

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