Prediction of non-hydrocarbon gas components in separator by using Hybrid Computational Intelligence models-Reference-Cited by-同舟云学术

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Prediction of non-hydrocarbon gas components in separator by using Hybrid Computational Intelligence models

Published:2015-11-24 Issue:4 Volume:28 Page:635-649
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Helmy Tarek,Hossain Muhammad Imtiaz,Adbulraheem Abdulazeez,Rahman S. M.,Hassan Md. Rafiul,Khoukhi Amar,Elshafei M.

Funder

King Abdulaziz City for Science and Technology (SA)

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/content/pdf/10.1007/s00521-015-2088-4.pdf

Reference52 articles.

1. Al-Anazi A, Gates ID (2010) A support vector machine algorithm to classify lithofacies and model permeability in heterogeneous reservoirs. Eng Geol 114(3–4):267–277

2. Al-Anazi A, Gates ID, Azaiez J (2009) Innovative data-driven permeability prediction in a heterogeneous reservoir. In: SPE EUROPEC/EAGE annual conference and exhibition, Amsterdam, The Netherlands

3. Al-Farhan FA, Ayala LF (2006) Optimization of surface condensate production from natural gases using artificial intelligence. J Petrol Sci Eng 53(1–2):135–147

4. Ali M, Chawathe A (2000) Using artificial intelligence to predict permeability from petrographic data. Comput Geosci 26:915–925

5. Almeida MB, Braga AP, Braga JP (2000) SVM-KM: speeding SVMs learning with a priori cluster selection and k-means. In: Proceedings of the 6th Brazilian symposium on neural networks, pp 162–167

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