کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5006941 1461492 2017 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Modeling of the microstructural properties of (x)ZnO(1 − x)Fe2O3 nanocrystallines by artificial neural network and response surface methodology
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
Modeling of the microstructural properties of (x)ZnO(1 − x)Fe2O3 nanocrystallines by artificial neural network and response surface methodology
چکیده انگلیسی
In this work, artificial neural network and response surface methodology (RSM) models were developed for the analysis and prediction of the microstructural properties (x)ZnO(1 − x)Fe2O3 nanocrystallines produced by mechanical milling process. The input parameters are milling times and concentration. The lattice parameters (a,c) and crystallite size are the outputs of the models. The ability of ANN and RSM methods for the optimization of mechanical milling process is investigated. The results of two methods were compared based on their predictive capabilities in terms of the coefficient of determination (R2). It was found that ANN model is much more accurate in prediction as compared to RSM even the small numbers of experiments.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Measurement - Volume 95, January 2017, Pages 70-76
نویسندگان
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