摘要
智能优化算法通过模拟自然生态系统机制以解决复杂优化问题,粒子滤波成为解决非线性及非高斯动态系统最优估计问题的研究热点。若将多种优化算法结合使用,设计更好的滤波器参数寻优步骤,将会极大改善现有非线性滤波的估计性能。介绍了几种智能计算方法和粒子滤波方法,在此基础上,对智能优化方法与粒子滤波技术的融合进行了分析和讨论,并加以总结和展望。
With simulating the mechanism of nature ecosystem, the intelligent computational approaches have the superiority to solve the combined optimal problem over traditional methods. Particle filtering is used widely to solve the optimized estimates of non-linear and non-Gaussian dynamic system. If the intelligent computational approaches and the particle filtering are combined together, we believe that the estimate performance of the non-linear filtering will improve greatly. In this paper, we introduce some popular intelligent computational approaches and particle filtering, analyze their advantages and disadvantages, introduce their research progress and applied area. Then the integrated problem of the intelligent computational approaches and the particle filtering are analyzed and discussed. At last, the summary and prospects of the integrated application of the intelligent computational approaches and the particle filtering technique area given.
出处
《海洋测绘》
2009年第2期74-77,共4页
Hydrographic Surveying and Charting
基金
国家自然科学基金(40474007)
国家杰出青年科学基金(40125013)
关键词
遗传算法
模拟退火算法
粒子群算法
蚁群算法
粒子滤波
genetic algorithm
simulated annealing algorithm
particle swarm optimization algorithm
ant colony algorithm
particle Filtering
