In this paper,we have presented a new PSO algorithm,improved velocity mutation particle swarm optimizer(iPSOVMO).
论文提出了一种新的PSO算法——改进的速度变异粒子群算法（iPSOVMO）。
参考来源 - 期刊学术社区·2,447,543篇论文数据，部分数据来源于NoteExpress
The analysis of the walking state of bilateral leg was focused on in gait switching. The reason of velocity mutation was summarized.
最后，重点分析了该四足机器人双侧腿部进行步态切换时的行走状态，总结出了其速度曲线突变的原因。
For improving the predicting results, two improved PSO algorithm are presented also in this paper: Velocity Mutation PSO and hybrid PSO.
在此基础上，进一步提出了混合粒子群算法和速度变异粒子群算法两种改进算法提高优化性能。
The minimum boundary mutation can limit the scope of particles' position and velocity, as well as keep the direction of them.
而最小值边界变异既能有效地限制了粒子位置或速度的幅值，同时可以保持粒子的飞行方向。
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