کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7562448 | 1491508 | 2017 | 35 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
SRO_ANN: An integrated MatLab toolbox for multiple surface response optimization using radial basis functions
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
SRO_ANN, a MatLab® toolbox for implementing multiple surface response optimization by artificial neural networks (SRO_ANN) is presented. Radial basis functions, a type of artificial neural networks, are applied through an easily managed graphical user interface. A detailed description of the interface is provided, including a simulated and two literature examples which allow one to show the potentiality of the software. The discussed experimental examples correspond to: (1) the maximization of the research octane number (RON) of fuels, influenced by three factors (reaction temperature, operating pressure and low liquid hourly space velocity), and (2) the optimization of the calcification process for diced tomatoes, evaluated through three different responses (calcium content, firmness and pH), which are affected by three factors (calcium concentration, solution temperature and treatment time). The results show that the application of a nonparametric tool can enhance the performance of optimization modeling tasks.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 171, 15 December 2017, Pages 198-206
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 171, 15 December 2017, Pages 198-206
نویسندگان
Pablo C. Giordano, Héctor C. Goicoechea, Alejandro C. Olivieri,