International Journal of Computational Intelligence Systems

Volume 6, Issue 2, March 2013, Pages 198 - 208

A Hybrid Approach Based on the Combination of Adaptive Neuro-Fuzzy Inference System and Imperialist Competitive Algorithm: Oil Flow Rate of the Wells Prediction Case Study

Authors
Shahram Mollaiy Berneti
Corresponding Author
Shahram Mollaiy Berneti
Received 15 March 2012, Accepted 15 August 2012, Available Online 1 March 2013.
DOI
https://doi.org/10.1080/18756891.2013.768430How to use a DOI?
Keywords
ANFIS, Imperialist Competitive Algorithm, Gradient Descent, Oil Flow Rate
Abstract

In this paper, a novel hybrid approach composed of adaptive neuro-fuzzy inference system (ANFIS) and imperialist competitive algorithm is proposed. The imperialist competitive algorithm (ICA) is used in this methodology to determine the most suitable initial membership functions of the ANFIS. The proposed model combines the global search ability of ICA with local search ability of gradient descent method. To illustrate the suitability and capability of the proposed model, this model is applied to predict oil flow rate of the wells utilizing data set of 31 wells in one of the northern Persian Gulf oil fields of Iran. The data set collected in a three month period for each well from Dec. 2002 to Nov. 2010. For the sake of performance evaluation, the results of the proposed model are compared with the conventional ANFIS model. The results show that the significant improvements are achievable using the proposed model in comparison with the results obtained by conventional ANFIS.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
6 - 2
Pages
198 - 208
Publication Date
2013/03/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.1080/18756891.2013.768430How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Shahram Mollaiy Berneti
PY  - 2013
DA  - 2013/03/01
TI  - A Hybrid Approach Based on the Combination of Adaptive Neuro-Fuzzy Inference System and Imperialist Competitive Algorithm: Oil Flow Rate of the Wells Prediction Case Study
JO  - International Journal of Computational Intelligence Systems
SP  - 198
EP  - 208
VL  - 6
IS  - 2
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2013.768430
DO  - https://doi.org/10.1080/18756891.2013.768430
ID  - MollaiyBerneti2013
ER  -