引入四元数理论的改进粒子群算法

为了解决传统粒子群算法存在早熟收敛、搜索空间受限、精度不高等问题,通过四元数理论和粒子群算法,提出了一种改进粒子群算法.该算法以树状拓扑结构为基础建立邻域结构,速度公式中分别使用粒子三部分的记忆值,即自身最佳、局部最佳及全局最佳,同时在社会部分加入以四元数为模型的三者之间关系项,这样既能记录三者单纯的比较结果,又可...

An improved particle swarm optimization algorithm based on quaternion theory

In order to solve the problems of traditional particle swarm optimization such as premature convergence, limited search space, and low accuracy, an improved particle swarm optimization algorithm is proposed through quaternion theory and particle swarm optimization. A neighborhood structure based on a tree-like topology has built. The memory values of the three parts of the particle are used in the speed formula, that is, the best self, local best, and global best. At the same time, the quaternion is added to the social part. The number is the relationship between the three of the model, so that both the simple comparison results of the three can be recorded, and the relationship between the three can also be recorded. Finally, the convergence and effectiveness of the algorithm are verified from three aspects: theoretical proof, experimental simulation and actual physical experiment. The results show that the proposed new algorithm can converge to the global optimal value in some test functions, and the average value of other functions is lower than the other three, this algorithm is closer to the global optimal, at the same time, it has obvious advantages in the application of image contrast enhancement.