基于人群搜索的极限学习机荷电状态估计

Extreme Learning Machine SOC estimation based on seeker optimization

以电池组的电压、充放电电流作为输入变量,SOC作为输出变量。在建模过程中,用人群搜索算法来优化随机给定的极限学习机的输入权值矩阵和偏差。

With the battery voltage,charge and discharge current as input variables,and state of current(SOC)as output variables.Seeker optimization algorithm is used to modify the input weightmatrix and bias of the extreme learning machine,when a random model is established.