中文摘要：

针对人工鱼群算法中固定的视野和步长导致算法寻优速度变慢、易陷入局部最优等问题,引入了一个变系数因子来自适应调节人工鱼在聚群、追尾和觅食行为中的视野和步长;此外,为了降低算法后期运算复杂度以获得更多有效的人工鱼,加入一种人工鱼群最大迭代次数淘汰机制。将改进后的人工鱼群算法用来优化支持向量机中的核函数参数和惩罚参数,并应用到风电场短期风电功率预测中。通过实验仿真对比得出改进的人工鱼群优化支持向量机在短期风电功率预测中有较好的效果。

英文摘要：

Due to the fixed vision and step of artificial fish swarm algorithm resulting in algorithm optimization speed is slow,and easy to fall into local optimum value,it introduces a variable coefficient factor for adapting the vision and step of artificial fish in swarm,rear end and foraging behavior. In addition,a maximum number of iterations elimination mechanism is added to reduce computational complexity of late algorithm and obtain more effective artificial fish.Then,the improved artificial fish swarm algorithm is used to optimize the kernel function and penalty coefficient of support vector machine,and applied it in short-term wind power prediction. The simulation results show that the improved artificial fish swarm algorithm optimization support vector machine has a better effect on short-term wind power prediction.