کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5147614 | 1497355 | 2017 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
H2-selective mixed matrix membranes modeling using ANFIS, PSO-ANFIS, GA-ANFIS
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کلمات کلیدی
MMMsANNMSREPDMSMFSRMSEFCMANFISGenetic algorithm - الگوریتم ژنتیکParticle swarm optimization - بهینه سازی ازدحام ذراتPSO - بهینه سازی ازدحام ذراتmembership functions - توابع عضویتHydrogen separation - جداسازی هیدروژنRoot mean square error - ریشه میانگین خطای مربعAdaptive neuro-fuzzy inference system - سیستم استنتاج فازی عاملی سازگارartificial neural networks - شبکه های عصبی مصنوعیcoefficient of determination - ضریب تعیینAARD - طبیعتMembrane - غشاءMixed matrix membranes - غشاهای ماتریکس مخلوطFuzzy C-means clustering - فازی C به معنای خوشه بندی استFuzzy logic - منطق فازیPolydimethylsiloxane - پلیمتیلسیلوکسان
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
الکتروشیمی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
The novel contribution of the current study is to employ adaptive neuro-fuzzy inference system (ANFIS) for evaluation of H2-selective mixed matrix membranes (MMMs) performance in various operational conditions. Initially, MMMs were prepared by incorporating zeolite 4A nanoparticles into polydimethylsiloxane (PDMS) and applied in gas permeation measurement. The gas permeability of CH4, CO2, C3H8 and H2 was used for ANFIS modeling. In this manner, the H2/gas selectivity as the output of the model was modeled to the variations of feed pressure, nanofiller contents and the kind of gas, which were defined as input (design) variables. The proposed method is based on the improvement of ANFIS with genetic algorithm (GA) and particle swarm optimization (PSO). The PSO and GA were applied to improve the ANFIS performance. To determine the efficiency of PSO-ANFIS, GA-ANFIS and ANFIS models, a statistical analysis was performed. The results revealed that the PSO-ANFIS model yields better prediction in comparison to two other methods so that root mean square error (RMSE) and coefficient of determination (R2) were obtained as 0.0135 and 0.9938, respectively. The RMSE and R2 values for GA-ANFIS were 0.0320 and 0.9653, respectively, and for ANFIS model were 0.0256 and 0.9787, respectively.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Hydrogen Energy - Volume 42, Issue 22, 1 June 2017, Pages 15211-15225
Journal: International Journal of Hydrogen Energy - Volume 42, Issue 22, 1 June 2017, Pages 15211-15225
نویسندگان
Mashallah Rezakazemi, Amir Dashti, Morteza Asghari, Saeed Shirazian,