At present the advanced technology expensing is used mostly in the management system of canteen in the domestic and foreign. The technologies are contacting IC card, the non-contacting IC card and the RS485 bus. But t...
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In this paper, designing scheme of unit access controlsystem are proposed. MO4 fingerprint identification module is basis of this scheme and single-chip machine is control center of this scheme. In the scheme design ...
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This paper designs a Neighborhood Security system based on the ZigBee technology. Composed of user nodes, routers and central nodes, the entire system constitutes a wireless network with safe reliability and stable pe...
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In this paper, releasing range model of traffic guidance information is formulated based on combinatorial optimization by the correlation analysis of road traffic flow in time and space. As it is hard to get the optim...
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In this paper, releasing range model of traffic guidance information is formulated based on combinatorial optimization by the correlation analysis of road traffic flow in time and space. As it is hard to get the optimal solution in a limited time through analysis, a greedy algorithm and a simulated annealing (SA) based algorithm are presented to solve the model. Some traffic flow data detected by remote microwave sensors in some road links in Beijing urban expressway are employed to compare the two algorithms. The results show that SA based algorithm has achieved better result even its running time is little longer than the greedy algorithm. Therefore the proposed SA based algorithms can be used to improve the pertinency, validity and automation of releasing traffic guidance information.
In this paper, releasing range model of traffic guidance information is formulated based on combinatorial optimization by the correlation analysis of road traffic flow in time and space. As it is hard to get the optim...
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ISBN:
(纸本)9787894631046
In this paper, releasing range model of traffic guidance information is formulated based on combinatorial optimization by the correlation analysis of road traffic flow in time and space. As it is hard to get the optimal solution in a limited time through analysis, a greedy algorithm and a simulated annealing (SA) based algorithm are presented to solve the model. Some traffic flow data detected by remote microwave sensors in some road links in Beijing urban expressway are employed to compare the two algorithms. The results show that SA based algorithm has achieved better result even its running time is little longer than the greedy algorithm. Therefore the proposed SA based algorithms can be used to improve the pertinency, validity and automation of releasing traffic guidance information.
Occupant's identity and location are important information for lighting control in order to reduce the energy consumption while increasing livelihood. While active RFID system provides occupant's identity, it ...
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Occupant's identity and location are important information for lighting control in order to reduce the energy consumption while increasing livelihood. While active RFID system provides occupant's identity, it is nontrivial to localize the occupant's location in an indoor environment due to the multipath effect, the changing environment, and the unreliable communication link. In this paper, we implement a system with multiple active RFID readers, and develop a localization algorithm based on support vector machine (SVM). The algorithm uses round-robin comparison to localize the occupant to one of the multiple regions in a floor. The geometric relationship among the rooms and the historical localization data are used to further improve the localization accuracy. Numerical results demonstrate a high localization accuracy of this algorithm. We hope this work sheds insight on lighting control for energy saving and an increased livelihood.
Current travel time prediction algorithms often need large numbers of travel time data, which are difficult to gain and highly cost, to identify the algorithms' parameters. In this paper, we propose new travel tim...
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ISBN:
(纸本)9781617387777
Current travel time prediction algorithms often need large numbers of travel time data, which are difficult to gain and highly cost, to identify the algorithms' parameters. In this paper, we propose new travel time prediction algorithms, which use neural network to predict future speed dynamically, and use data fusion to integrate the speed data of different detectors and, to calculate the travel time. Vehicle plate recognition technology is used to collect the real travel time of the test section on Beijing Third-Ring freeway to evaluate the algorithms. From the obtained results, the average prediction error is less than 10%.
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