Search

In order to increase the accuracy of off-line map matching algorithm in transport networks,and avoid matching a wrong link,the idea of iteration at the route node is proposed based on the principle of multi-route. The algorithm includes six steps: data pre-process,subnetwork generation,initial chosen route generation,associative matrix between nodes and links generation,generation of consideration set of routes and final chosen route. The detailed process of the proposed algorithm is referred in this paper,which is simple and easy to implement. The algorithm is used to process GPS data in Minneapolis-St. Paul Metropolitan area. From the application of the algorithm,it can be found that the accuracy is on a high level in total and decrease as the distance getting longer. And compared with the matching algorithm based on the shortest path,it is found that the accuracy of the algorithm in this paper is much better,especially when the distance is long. [ABSTRACT FROM AUTHOR]

Sunshine has played a critical role in trajectory analysis. It is of great significance to design an algorithm that could not only estimate the sunshine information of the trajectory effectively, but also remove the redundant points and keep the necessary sunshine-based information. This paper proposes a sunshine based trajectory simplification algorithm, which considers the urban trajectory character, to solve the challenges of trajectory analyzing in various sunshine related scenarios. On the one hand, an orientation model is established to abstract the relationship between trajectory and sunlight. On the other hand, a sunshine related trajectory simplification model is proposed, and the genetic algorithm is applied to find the points that need to be reserved. Finally, the real-world data of Minneapolis, US, is used for experiment. The results demonstrate that the proposed algorithm can effectively reduce the number of turning points in the trajectories under the control of bound Tmax. [ABSTRACT FROM AUTHOR]

Sequential sensing algorithms are developed for OFDM-based hierarchical cognitive radio (CR) systems. Secondary users sense multiple subbands simultaneously for possible spectrum availabilities under hard misdetection constraints to prevent interference to the primary users. Accounting for the fact that the sensing time overhead can often be significant, a novel performance metric is introduced based on the effective achievable data rate. An optimization problem is formulated in the framework of optimal stopping problems to maximize the average effective data rate by determining the best time to stop taking samples and proceed to data transmission. A basis expansion-based suboptimal algorithm is developed to reduce the prohibitive complexity of the optimal solution. The numerical results presented verify the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]