• 论文 •

### 基于自适应在线极限学习机模型的预测方法

• 出版日期:2016-07-15 发布日期:2016-07-06

### Study on Prediction Method Based on Adaptive Ensemble Online Sequential Extreme learning machine

Xu Yong et al.

• Online:2016-07-15 Published:2016-07-06

Abstract:

Since the single online sequential extreme learning machine's performance is unstable, it propose an adaptive and selective OSELM. Firstly，it initializes the multiple online sequential extreme learning machine model, then adjustes adaptively the integrated weight of every online sequential extreme learning machine according to their training error and variance for each batch of data, and deletes the model that its integrated weight is smaller than the threshold to improve the training speed dynamically. Finally, the high accuracy and good generalization's model will be selected for integrated prediction. Experimental results show that the ASE-OSELM has higher forecast accuracy and generalization ability than BPNN、LS-SVM and OSELM.