Fault diagnosis of rotary kiln using SVM and binary ACO. Kadri, O., Mouss, L. H., & Mouss, M. D. Journal of Mechanical Science and Technology, 26(2):601–608, 2012. ![Fault diagnosis of rotary kiln using SVM and binary ACO [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex This paper proposes a novel hybrid algorithm for fault diagnosis of rotary kiln based on a binary ant colony (BACO) and support vector machine (SVM). The algorithm can find a subset selection which is attained through the elimination of the features that produce noise or are strictly correlated with other already selected features. The BACO algorithm can improve classification accuracy with an appropriate feature subset and optimal parameters of SVM. The proposed algorithm is easily implemented and because of use of a simple filter in that, its computational complexity is very low. The performance of the proposed algorithm is evaluated through two real Rotary Cement kiln datasets. The results show that our algorithm outperforms existing algorithms.
@article{kadri_fault_2012,
title = {Fault diagnosis of rotary kiln using {SVM} and binary {ACO}},
volume = {26},
issn = {1976-3824},
url = {https://doi.org/10.1007/s12206-011-1216-z},
doi = {10.1007/s12206-011-1216-z},
abstract = {This paper proposes a novel hybrid algorithm for fault diagnosis of rotary kiln based on a binary ant colony (BACO) and support vector machine (SVM). The algorithm can find a subset selection which is attained through the elimination of the features that produce noise or are strictly correlated with other already selected features. The BACO algorithm can improve classification accuracy with an appropriate feature subset and optimal parameters of SVM. The proposed algorithm is easily implemented and because of use of a simple filter in that, its computational complexity is very low. The performance of the proposed algorithm is evaluated through two real Rotary Cement kiln datasets. The results show that our algorithm outperforms existing algorithms.},
number = {2},
journal = {Journal of Mechanical Science and Technology},
author = {Kadri, Ouahab and Mouss, Leila Hayet and Mouss, Mohamed Djamel},
year = {2012},
pages = {601--608},
}
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