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Deep learning for short-term traffic flow prediction [PDF]
Transportation Research Part C: Emerging Technologies, 2017 We develop a deep learning model to predict traffic flows. The main contribution is development of an architecture that combines a linear model that is fitted using $\ell_1$ regularization and a sequence of $\tanh$ layers. The challenge of predicting traffic flows are the sharp nonlinearities due to transitions between free flow, breakdown, recovery ...
Polson, Nicholas, Sokolov, Vadim
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Short-Term Traffic Flow Prediction Method Based on Spatiotemporal Relativity [PDF]
Jisuanji gongcheng, 2020 The intelligent travel of the new generation intelligent traffic system and the intelligent decision-making of traffic big data need accurate and timely short-term traffic flow prediction.Deep learning can generate features by machine learning technology,
YAN Yang, SUN Lijun, ZHU Lanting
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Prediction model for short‐term traffic flow based on a K‐means‐gated recurrent unit combination
IET Intelligent Transport Systems, 2022 Short‐term forecasting of traffic flow is an indispensable part of easing traffic pressure. Considering that different traffic flow patterns will affect the short‐term traffic flow prediction results, a combined method based on the K‐means clustering ...
Zhaoyun Sun +4 more
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A combined method for short-term traffic flow prediction based on recurrent neural network
Alexandria Engineering Journal, 2021 The accurate prediction of real-time traffic flow is indispensable to intelligent transport systems. However, the short-term prediction remains a thorny issue, due to the complexity and stochasticity of the traffic flow.
Saiqun Lu +3 more
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Advances in Civil Engineering, 2021 Real-time expressway traffic flow prediction is always an important research field of intelligent transportation, which is conducive to inducing and managing traffic flow in case of congestion.
Chunyan Shuai +3 more
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Forecasting bus passenger flows by using a clustering-based support vector regression approach [PDF]
, 2020 As a significant component of the intelligent transportation system, forecasting bus passenger flows plays a key role in resource allocation, network planning, and frequency setting.
Bai, Yun +3 more
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An accurate traffic flow prediction using long-short term memory and gated recurrent unit networks [PDF]
, 2023 Congestion on roadways is an issue in many cities, especially at peak times, which causes air and noise pollution and cause pressure on citizens. So, the implementation of intelligent transportation systems (ITSs) is a very important part of smart cities.
Hussein, Shereen A. +3 more
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Short-term traffic flow prediction: An ensemble machine learning approach
Alexandria Engineering Journal, 2023 The inconvenience of travel, air pollution and consequent economic losses caused by traffic congestion have seriously restricted the healthy and sustainable development of cities in China.
Guowen Dai, Jinjun Tang, Wang Luo
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IEEE Access, 2020 Accurate prediction of traffic flow in urban networks is of great significance for smart city management. A short-term traffic flow prediction algorithm of Quantum Genetic Algorithm - Learning Vector Quantization (QGA-LVQ) neural network is proposed to ...
Fuquan Zhang +6 more
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Journal of Harbin University of Science and Technology, 2019 We employ the long/shortterm memory (LSTM) recurrent neural network to analyze the impact of various input settings on shortterm traffic flow prediction performance First, we compared the shortterm traffic flow prediction performance for different ...
MAN Chun-tao, KANG Dan-qing
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