کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1138335 | 1489209 | 2007 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Modelling public transport trips by radial basis function neural networks
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
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چکیده انگلیسی
Artificial neural networks (ANNs) are one of the recently explored advanced technologies, which show promise in the area of transportation engineering. The presented study used two different ANN algorithms, feed forward back-propagation (FFBP) and radial basis function (RBF), for the purpose of daily trip flow forecasting. The ANN predictions were quite close to the observations as reflected in the selected performance criteria. The selected stochastic model performance was quite poor compared with ANN results. It was seen that the RBF neural network did not provide negative forecasts in contrast to FFBP applications. Besides, the local minima problem faced by some FFBP algorithms was not encountered in RBF networks.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mathematical and Computer Modelling - Volume 45, Issues 3–4, February 2007, Pages 480–489
Journal: Mathematical and Computer Modelling - Volume 45, Issues 3–4, February 2007, Pages 480–489
نویسندگان
Hilmi Berk Celikoglu, Hikmet Kerem Cigizoglu,