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Traffic Flow-Big Data Forecasting Method Based on Spatial-Temporal Weight Correlation
Xin LI, Qing LUO, Deyou MENG
Acta Scientiarum Naturalium Universitatis Pekinensis    2017, 53 (4): 775-782.   DOI: 10.13209/j.0479-8023.2017.040
Abstract1009)   HTML9)    PDF(pc) (29192KB)(163)       Save

A distributed incremental aggregation method combined with traffic flow data cleansing rules is proposed, and it can provide more accurate and reliable data for traffic flow forecast analysis. Through the correlation analysis of traffic flow in road network, the authors used the multi-allocation of turning rate in the intersection to build the spatial weight matrix, and improved the STARIMA traffic flow forecasting model. The experiment result proves that this method can meet the needs of traffic flow big-data forecasting in the efficiency and accuracy, and provide the basis for the traffic routing information.

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ReSim: A Simulator Platform for Reconfigurable Processor
DAI Peng,WEI Lai,XIN Lingxuan,WANG Xin’an,ZHANG Xing
Acta Scientiarum Naturalium Universitatis Pekinensis   
Abstract1224)            Save
A hierarchically modularized design based clock accurate simulator platform ReSim is proposed for the flexible interconnection, expandability and dense computational characteristics of reconfigurable processor ReMAP. The simulator is designed under three hierarchy software framework, which contains interconnect modules to accelerate various interconnection architecture evaluation, control modules to simulate different compute model. The simulator can quickly establish the reconfigurable processor model and test the function validity of processor architecture, as well as evaluating the performance under the control of clock driving module for the whole system. The result shows that ReSim can support the evaluation and simulation of the reconfigurable processor architecture ReMAP-2 effectively.
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