IJE TRANSACTIONS A: Basics Vol. 31, No. 10 (October 2018) 1617-1623   

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M. S. Lashkenari, A. KhazaiePoul, S. Ghasemi and M. Ghorbani
( Received: January 15, 2018 – Accepted in Revised Form: August 17, 2018 )

Abstract    This study investigates the potential of an intelligence model namely, Adaptive Neuro-Fuzzy Inference System (ANFIS) in prediction of the Zn metal ions adsorption in comparision with two well known empirical models included Thomas and Yoon methods. For this purpose, an organic-inorganic core/shell structure, γ-Fe2O3/polyrhodanine nanocomposite with γ-Fe2O3 nanoparticle as core with average diameter of 15 nm and polyrhodanine as shell with thickness of 3 nm, was synthesized via chemical oxidation polymerization. The properties of adsorbent were characterized with transmission electron microscope (TEM) and Fourier transform infrared (FT-IR) spectroscopy. Sixty seven experimental data sets including the treatment time (t), the initial concentration of Zn (Co), column height (h) and flow rate (Q) were used as input data to predict the ratios of effluent-to-influent concentrations of Zn (Ct/C0). The results showed that ANFIS model with the R coefficient of 0.99 can predict Ct/C0 more accurately than empirical models. Also it was found that the result of the Thomas and Yoon methods with R coefficient of 0.828 and 0.829, respectively were so close to each other. Finally, performance of our ANFIS model was compare to Thomas and Yoon methods in two different conditions, i.e. variable initial influent concentration and variable column height. High performance of ANFIS model was proved by the comparitive results.


Keywords    Adaptive Neuro-fuzzy Inference System, Adsorption, γ-Fe2O3, Polyrhodanine, Fixed Bed Column



این مطالعه به بررسی عملکزد مدل هوشمند سیستم استنتاج عصبی-فازی سازگار در پیشبینی جذب فلز روی و مقایسه آن با 2 مدل تجربی مشهور توماس و یون می پردازد. بدین منظور یک ساختار هسته و پوسته آلی/غیرآلی پلی رودانین/ γ-Fe2O3 که پوسته پلی رودانین ضخامت 3 نانومتر و هسته γ-Fe2O3 با متوسط قطر 15 نانومتر به روش پلیمریزاسیون شیمیایی تهیه گردید. خواص جاذب تهیه شده با استفاده از آزمون های میکروسکوپ الکترونی عبوری و اسپکتروسکوپی تبدیل فوریه مورد بررسی قرار گرفت. 67 مجموعه از داده های آزمایشگاهی شامل زمان آزمایش، غلظت اولیه روی، ارتفاع ستون و دبی جریان به عنوان داده های ورودی برای پیش بینی نسبت غلةت روی در خروجی به غلظت اولیه مورد استفاده قرار گرفت. نتایج نشان داد که مدل سیستم استنتاج عصبی-فازی سازگار با ضریب R برابر با 0.99 نسبت به دو مدل تجربی از دقت بالاتری برخوردار می‌باشد. همچنین مشخص گردید که نتایج مدل های توماس و یون به ترتیب با ضریب R برابر با 0.828 و 0.829 بسیار نزدیک به یکدیگر است. در نتایج نتایج مدل سیستم استنتاج عصبی-فازی سازگار با نتایج مدل های توماس و یون در دو حالت ارتفاع ستون جذب متغیر و غلظت اولیه متغیر مقایسه گردید. نتایج حاصل از مقایسه نشان دهنده عملکرد بهتر مدل سیستم استنتاج عصبی-فازی سازگار بوده است


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