Predictive model based on ANFIS for estimation of thermal conductivity of carbon dioxide

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• 作者：Afshin Tatar^a ; Ali Barati-Harooni^b ; Adel Najafi-Marghmaleki^b ; ^{adelnajafiput90@yahoo.com} ; Behzad Norouzi-Farimani^c ; Amir H Mohammadi^d ; ^e ; ^f ; ^{a.h.m@irgcp.fr} ; ^{amir_h_mohammadi@yahoo.com}
• 关键词：Thermal conductivity ; Adaptive neuro-fuzzy inference system (ANFIS) ; CO2 ; Conjugate ANFIS ; Model
• 刊名：Journal of Molecular Liquids
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：224
• 期：part_PB
• 页码：1266-1274
• 全文大小：1738 K
• 卷排序：224

文摘

We have developed an ANFIS model for CO2 thermal conductivity predictions. An extensive number of 1042 experimental data gathered from literature was used for model development. Combined Hybrid and Particle Swarm Optimization (PSO) methods were used to train the model. The predictions of the ANFIS model are successfully compared with two literature correlations. Results show that the developed model is accurate and effective in prediction of experimental data.