A Survey of Particle Swarm Optimization Applications in Electric Power Systems

System reliability analysis and optimization are important to efficiently utilize available resources and to develop an optimal system design architecture. System reliability optimization has been solved by using optimization techniques including met

粒子滤波算法在非线性系统中得到了广泛的应用，其精度取决于目标概率函数和重要性函数是否相近，并且样本退化问题也影响了算法的性能。针对粒子滤波算法中样本退化的问题，本文提出一种基于奇异值分解的粒子滤波算法。该算法通过使用奇异值分解方法得到的重要性概率密度函数更接近于目标概率分布，降低样本退化的影响，提高了滤波器的精度，然后在列车组合定位系统的数学模型中应用该算法进行仿真实验。 -Particle filter algorithm for nonlinear systems is widely use