The multipoint short-term traffic flow forecasting should deal with mass of historical traffic flow data from intersections in an area or urban. So the problem in runtime still remains to be the major obstacle for the...
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Pedestrians are key participants in transportation systems, so pedestrian detection in video surveillance systems is of great significance to the research and application of Intelligent Transportation systems (ITS). W...
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The key of designing MCMC algorithm is the choice of acceptance function. In this work, Selection criteria of acceptance function is given, and an improved Multi-point Metropolis algorithm with generic acceptance func...
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Interactive image segmentation which needs the user to give certain hard constraints has shown promising performance for object segmentation. In this paper, we consider characters in text image as a special kind of ob...
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This paper focuses on a class of unknown discrete-time nonlinear systems with dead-zone control constraints based on adaptive dynamic programming (ADP). The discrete-time Hamilton-Jacobi-Bellman (DTHJB) equation corre...
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Most objects with regular regions could be detected as Maximally Stable Extremal Regions (MSER) [20]. In this paper, We formulate object detection as a bi-label (object and non-object regions) segmentation problem, an...
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In this paper, an adaptive dynamic programming (ADP)-based self-learning algorithm is developed for solving the two-person zero-sum differential games for continuous-time nonlinear systems with saturating controllers....
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Over the last few years, Twitter is increasingly becoming an important source of up-to-date topics about what is happening in the world. In this paper, we propose a dynamic topic association detection model to discove...
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ISBN:
(纸本)9781450312301
Over the last few years, Twitter is increasingly becoming an important source of up-to-date topics about what is happening in the world. In this paper, we propose a dynamic topic association detection model to discover relations between Twitter topics, by which users can gain insights into richer information about topics of interest. The proposed model utilizes a time constrained method to extract event-based spatio-temporal topic association, and constructs a dynamic temporal map to represent the obtained result. Experimental results show the improvement of the proposed model compared to static spatio-temporal method and co-occurrence method. Copyright is held by the author/owner(s).
In this paper, a neural network (NN)-based adaptive dynamic programming (ADP) algorithm is employed to solve the optimal temperature control problem in the water-gas shift (WGS) process. Since the WGS process has char...
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In this paper, we solve the H∞ control problems for discrete-time affine nonlinear systems with known dynamics. An iterative heuristic dynamic programming algorithm is derived and the convergence analysis is provided...
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