ANFIS modeling of CO2 separation from natural gas using hollow fiber polymeric membrane. Issue 2 (17th January 2018)

• Record Type: Journal Article
• Authors: Baghban, Alireza; Azar, Ahmad Aref
• Is Part Of: Energy sources. Volume 40:Issue 2(2018)
• Page Start: 193
• Page End: 199
• Publication Date: 2018-01-17
• Subjects: ANFIS -- CO2 separation -- membrane -- natural gas -- polymer; Natural resources -- Periodicals; Energy consumption -- Periodicals; Energy consumption -- Climatic factors -- Periodicals; Energy conversion -- Periodicals; Energy conversion -- Environment aspects -- Periodicals; Power (Mechanics) -- Periodicals; 333.7905
• DOI: 10.1080/15567036.2017.1407845
• Languages: English
• ISSNs: 1556-7036

Abstract

ABSTRACT: The present study is proposed to develop the Adaptive Neuro-Fuzzy Inference System optimized by genetic algorithm to estimate CO2 value in permeate stream using a hollow fiber polymeric membrane for separation of binary gas containing CO2 and CH4 in natural gas. To that end, a number of 65 samples was gathered from the literature. Results indicated that the proposed ANFIS model has great potential with high correlation ( R 2 = 0.9993) and less error (RMSE = 0.0064) for estimation of aforementioned parameter.