کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7374967 1480064 2018 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Speed estimation of traffic flow using multiple kernel support vector regression
ترجمه فارسی عنوان
برآورد سرعت جریان ترافیک با استفاده از رگرسیون بردار چندگانه کرنل
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات فیزیک ریاضی
چکیده انگلیسی
Industrial loop detectors (ILDs) are the most common traffic detectors. In Shanghai, most of the ILDs are installed in a single loop way, which can detect various parameters, such as flow, saturation, and so on. However, they cannot detect the speed directly, which is one of the key inputs of intelligent transportation systems (ITS) for identifying the traffic state. Thus, this paper is dedicated to estimate speed accurately. It proposes a new algorithm that multiple kernel support vector regression (MKL-SVR) to complete this goal, which improves the accuracy and robustness of the speed estimation. Extensive experiments have been performed to evaluate the performances of MKL-SVR, compared with polynomial fitting, BP neural networks and SVR. All results indicate that the performances of MKL-SVR are the best and most robust.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physica A: Statistical Mechanics and its Applications - Volume 509, 1 November 2018, Pages 989-997
نویسندگان
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