کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5775716 1631745 2017 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Performance of small-world feedforward neural networks for the diagnosis of diabetes
ترجمه فارسی عنوان
عملکرد شبکه های عصبی فیدبک کوچک جهان برای تشخیص دیابت
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات ریاضیات کاربردی
چکیده انگلیسی
We investigate the performance of two different small-world feedforward neural networks for the diagnosis of diabetes. We use the Pima Indians Diabetic Dataset as input. We have previously shown than the Watts-Strogatz small-world feedforward neural network delivers a better classification performance than conventional feedforward neural networks. Here, we compare this performance further with the one delivered by the Newman-Watts small-world feedforward neural network, and we show that the latter is better still. Moreover, we show that Newman-Watts small-world feedforward neural networks yield the highest output correlation as well as the best output error parameters.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Mathematics and Computation - Volume 311, 15 October 2017, Pages 22-28
نویسندگان
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