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This paper presents a deep learning based time series model to predict the traffic flow of transportation systems, DeepTFP, which exploits the effectiveness of time series function in analyzing sequence data and deep learning in extracting traffic flow features. Accurate and timely prediction on the future traffic flow is strongly needed by individual travelers, public transport, and transport planning...
With the rapid growth of Web 2.0, social media has become a prevalent information sharing and spreading platform, where users can retweet interesting messages. To better understand the propagation mechanism for information diffusion, it is necessary to model the user retweeting behavior and predict future retweets. Some existing work in retweeting prediction based on matrix factorization focuses on...
Aimed at a class of large networked systems consisted of some subsystems which are not completely decoupling, with arbitrary bounded noise and constraints, this paper proposes a cooperation-based distributed model predictive control algorithm. Firstly, composite models combined of complete decoupling models and all interaction models are established, according to the interaction of subsystems. Afterwards,...
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