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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yang Jian-Bin Xu Wen-Bo |
| Copyright Year | 2011 |
| Abstract | In the applications of wireless sensor networks, the effects of data reflection largely depend on the accuracy of localization of the information collection node. Therefore, the position information of nodes is very important. Without it, events can not be sensed and measured, and value of application will be lost. To improve the location accuracy of nodes in wireless sensor networks, the paper puts forward research of node localization model in WSNs based on quantum particle swarm optimal algorithm. The results of the simulation show that the method can get significantly higher localization accuracy than the genetic algorithm and get the convergence of optimal solutions faster than the standard particle swarm algorithm under the same conditions. |
| Starting Page | 309 |
| Ending Page | 313 |
| File Size | 367436 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781457703270 |
| DOI | 10.1109/DCABES.2011.79 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-10-14 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wireless communication Wireless sensor networks Accuracy Quantum particle swarm optimization (QPSO) Node localization Educational institutions Particle swarm optimization Wireless sensor networks (WSNs) Particle swarm optimization(PSO) Genetic algorithms Convergence |
| Content Type | Text |
| Resource Type | Article |
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