کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
723349 | 892344 | 2006 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
SINGLE BLACK-BOX MODELS FOR TWO-POINT NON-INVASIVE TEMPERATURE PREDICTION
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مکانیک محاسباتی
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چکیده انگلیسی
In this paper the performance of a genetically selected radial basis functions neural network is evaluated for non-invasive two-point temperature estimation in a homogeneous medium, irradiated by therapeutic ultrasound at physiotherapeutic levels. In this work a single neural network was assigned to estimate the temperature profile at the two considered points, and more consistent results were obtained than when considering one model for each point. This result was possible by increasing the model complexity. The best model predicts the temperature from two unseen data sequences during approximately 2 hours, with a maximum absolute error less than 0.5 °C, as desired for a therapeutic temperature estimator.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: IFAC Proceedings Volumes - Volume 39, Issue 18, 2006, Pages 135–140
Journal: IFAC Proceedings Volumes - Volume 39, Issue 18, 2006, Pages 135–140
نویسندگان
C.A. Teixeira, M. Graça Ruano, A. E. Ruano, W.C.A. Pereira, C. Negreira,