| WSNs布局的粒子进化的多粒子群优化策略 |
| |
| 引用本文： | 林祝亮,马世平.WSNs布局的粒子进化的多粒子群优化策略[J].微电子学与计算机,2009,26(12). |
| |
| 作者姓名： | 林祝亮 马世平 |
| |
| 作者单位： | 1. 浙江师范大学,电气自动化研究中心,浙江,金华,321004;浙江工业大学,信息学院,浙江,杭州,310014
2. 浙江师范大学,电气自动化研究中心,浙江,金华,321004 |
| |
| 基金项目： | 浙江省教育厅资助项目 |
| |
| 摘 要： | 在粒子进化的多粒子群算法基础上,提出了一种无线传感网络节点布局的优化策略.该策略通过多个粒子群彼此独立地搜索解空间,提高了算法的寻优能力,有效地避免了"早熟"问题,提高了算法的稳定性.仿真实验表明,与传统的粒子群算法相比,该算法有效覆盖率由75.36%提高到80.96%,收敛速度提高了19.4%.因此粒子进化的多粒子群优化策略具有比传统的粒子群算法更好的优化效果.
|
| 关 键 词： | 无线传感网络 粒子群算法 有效覆盖率 粒子进化 |
The Strategy for Optimizing the Layout of WSNs Based on the Evolution of Multi-particle PSO |
| |
| LIN Zhu-liang,MA Shi-ping.The Strategy for Optimizing the Layout of WSNs Based on the Evolution of Multi-particle PSO[J].Microelectronics & Computer,2009,26(12). |
| |
| Authors: | LIN Zhu-liang MA Shi-ping |
| |
| Abstract: | It presents a strategy to achieve the optimization of layout node based on the evolution of multi-particle particle swarm optimization (PSO). The strategy adopted by the number of particles with each other independent groups to search for solutions space, to improve optimization of the algorithm ability to effectively avoid the "premature" to improve the stability of the algorithm. The simulation showed that the traditional PSO, the algorithm effective coverage by 75.36 percent to 80.96 percent, Convergence rate increased 19.4 percent. Therefore, the evolution of multi-particle PSO strategy than the traditional PSO has a better optimization results. |
| |
| Keywords: | WSNs PSO effective coverage rate particle evolution |
| 本文献已被 万方数据 等数据库收录！ |
|
