| Ladle Furnace Liquid Steel Temperature Prediction Model Based on Optimally Pruned Bagging | |
| Alternative Title | Ladle Furnace Liquid Steel Temperature Prediction Model Based on Optimally Pruned Bagging |
| Lue Wu1; Mao Zhizhong1; Yuan Ping1 | |
| 2012 | |
| Source Publication | JOURNAL OF IRON AND STEEL RESEARCH INTERNATIONAL
 |
| ISSN | 1006-706X |
| Volume | 19Issue:12Pages:21-28 |
| Abstract | For accurately forecasting the liquid steel temperature in ladle furnace (LF), a novel temperature prediction model based on optimally pruned Bagging combined with modified extreme learning machine (ELM) is proposed. By analyzing the mechanism of LF thermal system, a thermal model with partial linear structure is obtained. Subsequently, modified ELM, named as partial linear extreme learning machine (PLELM), is developed to estimate the unknown coefficients and undefined function of the thermal model. Finally, a pruning Bagging method is proposed to establish the aggregated prediction model for the sake of overcoming the limitation of individual predictor and further improving the prediction performance. In the pruning procedure, AdaBoost is adopted to modify the aggregation order of the original Bagging ensembles, and a novel early stopping rule is designed to terminate the aggregation earlier. As a result, an optimal pruned Bagging ensemble is achieved, which is able to retain Bagging's robustness against highly influential points, reduce the storage needs as well as speed up the computing time. The proposed prediction model is examined by practical data, and comparisons with other methods demonstrate that the new ensemble predictor can improve prediction accuracy, and is usually consisted compactly. |
| Other Abstract | For accurately forecasting the liquid steel temperature in ladle furnace (LF), a novel temperature prediction model based on optimally pruned Bagging combined with modified extreme learning machine (ELM) is proposed. By analyzing the mechanism of LF thermal system, a thermal model with partial linear structure is obtained. Subsequently, modified ELM, named as partial linear extreme learning machine (PLELM), is developed to estimate the unknown coefficients and undefined function of the thermal model. Finally, a pruning Bagging method is proposed to establish the aggregated prediction model for the sake of overcoming the limitation of individual predictor and further improving the prediction performance. In the pruning procedure, AdaBoost is adopted to modify the aggregation order of the original Bagging ensembles, and a novel early stopping rule is designed to terminate the aggregation earlier. As a result, an optimal pruned Bagging ensemble is achieved, which is able to retain Bagging's robustness against highly influential points, reduce the storage needs as well as speed up the computing time. The proposed prediction model is examined by practical data, and comparisons with other methods demonstrate that the new ensemble predictor can improve prediction accuracy, and is usually consisted compactly. |
| Keyword | ENSEMBLES NETWORKS Bagging extreme learning machine LF liquid steel temperature prediction model AdaBoost |
| Indexed By | CSCD |
| Language | 英语 |
| Funding Project | [Fundamental Research Funds for Central Universities of China] ; [National Natural Science Foundation of China] |
| CSCD ID | CSCD:4725263 |
| Citation statistics |
Cited Times:1[CSCD]
[CSCD Record]
|
| Document Type | 期刊论文 |
| Identifier | http://ir.imr.ac.cn/handle/321006/149345 |
| Collection | 中国科学院金属研究所 |
| Affiliation | 1.东北大学 2.中国科学院金属研究所 |
| Recommended Citation GB/T 7714 | Lue Wu,Mao Zhizhong,Yuan Ping. Ladle Furnace Liquid Steel Temperature Prediction Model Based on Optimally Pruned Bagging[J]. JOURNAL OF IRON AND STEEL RESEARCH INTERNATIONAL,2012,19(12):21-28. |
| APA | Lue Wu,Mao Zhizhong,&Yuan Ping.(2012).Ladle Furnace Liquid Steel Temperature Prediction Model Based on Optimally Pruned Bagging.JOURNAL OF IRON AND STEEL RESEARCH INTERNATIONAL,19(12),21-28. |
| MLA | Lue Wu,et al."Ladle Furnace Liquid Steel Temperature Prediction Model Based on Optimally Pruned Bagging".JOURNAL OF IRON AND STEEL RESEARCH INTERNATIONAL 19.12(2012):21-28. |
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