Research Article
An Incremental Learning Ensemble Strategy for Industrial Process Soft Sensors
Algorithm 1
Incremental learning ensemble strategy.
Input | |
(i) sub datasets are drawn from original data set. Here, , . | |
(ii) The number of sub learning machines is . | |
(iii) The coefficients of determination are and . | |
For | |
Initialize . Here, , is the amount of data. | |
For | |
(1) Calculate . is a distribution, and is the weight of . | |
(2) Randomly choose the training sub dataset and the testing sub dataset according to . | |
(3) The sub learning machine is trained by to obtain a soft sensor model . | |
(4) Calculate the error of using and : | |
(5) Calculate the error rate . If , give up , and return to step (2). | |
(6) Calculate , where or 3. Obtain the ensemble soft sensor model according to : | |
(7) Calculate the error of using . If , give up , and return to step (2). | |
(8) Calculate to update the weights: | |
Output: Obtain the ensemble soft sensor model according to : | |