Taguchi's T-method with nearest integer-based binary bat algorithm for prediction
Taguchi’s T-method is a new prediction technique under the Mahalanobis-Taguchi system to predict unknown output or future states based on available historical information. Conventionally, in optimizing the T-method prediction accuracy, Taguchi’s orthogonal array is utilized to determine a subset of...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Institute of Advanced Engineering and Science (IAES)
2022
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/98605/1/KhairurRijalJamaludin2022_TaguchisTMethodwithNearestInteger.pdf |
| _version_ | 1796866653805346816 |
|---|---|
| author | Marlan, Zulkifli Marlah Jamaludin, Khairur Rijal Ramlie, Faizir Harudin, Nolia |
| author_facet | Marlan, Zulkifli Marlah Jamaludin, Khairur Rijal Ramlie, Faizir Harudin, Nolia |
| author_sort | Marlan, Zulkifli Marlah |
| collection | ePrints |
| description | Taguchi’s T-method is a new prediction technique under the Mahalanobis-Taguchi system to predict unknown output or future states based on available historical information. Conventionally, in optimizing the T-method prediction accuracy, Taguchi’s orthogonal array is utilized to determine a subset of significant features to be used in formulating the optimal prediction model. This, however, resulted in a sub-optimal prediction accuracy due to its fixed and limited feature combination offered for evaluation and lack of higher-order feature interaction. In this paper, a swarm-based binary bat optimization algorithm with a nearest integer discretization approach is integrated with the Taguchi’s T-method. A comparative study is conducted by comparing the performance of the proposed method against the conventional approach using mean absolute error as the performance measure on four benchmark case studies. The results from experimental studies show a significant improvement in the T-method prediction accuracy. A reduction in the total number of features results in a less complex model. Based on the general observation, the nearest integer-based binary bat algorithm successfully optimized the selection of significant features due to recursive and repetitive searchability, in addition to its adaptive element in response to the current best solution in guiding the search process towards optimality. |
| first_indexed | 2024-03-05T21:15:23Z |
| format | Article |
| id | utm.eprints-98605 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T21:15:23Z |
| publishDate | 2022 |
| publisher | Institute of Advanced Engineering and Science (IAES) |
| record_format | dspace |
| spelling | utm.eprints-986052023-01-25T09:29:29Z http://eprints.utm.my/98605/ Taguchi's T-method with nearest integer-based binary bat algorithm for prediction Marlan, Zulkifli Marlah Jamaludin, Khairur Rijal Ramlie, Faizir Harudin, Nolia QA Mathematics QA75 Electronic computers. Computer science Taguchi’s T-method is a new prediction technique under the Mahalanobis-Taguchi system to predict unknown output or future states based on available historical information. Conventionally, in optimizing the T-method prediction accuracy, Taguchi’s orthogonal array is utilized to determine a subset of significant features to be used in formulating the optimal prediction model. This, however, resulted in a sub-optimal prediction accuracy due to its fixed and limited feature combination offered for evaluation and lack of higher-order feature interaction. In this paper, a swarm-based binary bat optimization algorithm with a nearest integer discretization approach is integrated with the Taguchi’s T-method. A comparative study is conducted by comparing the performance of the proposed method against the conventional approach using mean absolute error as the performance measure on four benchmark case studies. The results from experimental studies show a significant improvement in the T-method prediction accuracy. A reduction in the total number of features results in a less complex model. Based on the general observation, the nearest integer-based binary bat algorithm successfully optimized the selection of significant features due to recursive and repetitive searchability, in addition to its adaptive element in response to the current best solution in guiding the search process towards optimality. Institute of Advanced Engineering and Science (IAES) 2022-08 Article PeerReviewed application/pdf en http://eprints.utm.my/98605/1/KhairurRijalJamaludin2022_TaguchisTMethodwithNearestInteger.pdf Marlan, Zulkifli Marlah and Jamaludin, Khairur Rijal and Ramlie, Faizir and Harudin, Nolia (2022) Taguchi's T-method with nearest integer-based binary bat algorithm for prediction. Bulletin of Electrical Engineering and Informatics, 11 (4). pp. 2215-2224. ISSN 2089-3191 http://dx.doi.org/10.11591/eei.v11i4.3859 DOI:10.11591/eei.v11i4.3859 |
| spellingShingle | QA Mathematics QA75 Electronic computers. Computer science Marlan, Zulkifli Marlah Jamaludin, Khairur Rijal Ramlie, Faizir Harudin, Nolia Taguchi's T-method with nearest integer-based binary bat algorithm for prediction |
| title | Taguchi's T-method with nearest integer-based binary bat algorithm for prediction |
| title_full | Taguchi's T-method with nearest integer-based binary bat algorithm for prediction |
| title_fullStr | Taguchi's T-method with nearest integer-based binary bat algorithm for prediction |
| title_full_unstemmed | Taguchi's T-method with nearest integer-based binary bat algorithm for prediction |
| title_short | Taguchi's T-method with nearest integer-based binary bat algorithm for prediction |
| title_sort | taguchi s t method with nearest integer based binary bat algorithm for prediction |
| topic | QA Mathematics QA75 Electronic computers. Computer science |
| url | http://eprints.utm.my/98605/1/KhairurRijalJamaludin2022_TaguchisTMethodwithNearestInteger.pdf |
| work_keys_str_mv | AT marlanzulkiflimarlah taguchistmethodwithnearestintegerbasedbinarybatalgorithmforprediction AT jamaludinkhairurrijal taguchistmethodwithnearestintegerbasedbinarybatalgorithmforprediction AT ramliefaizir taguchistmethodwithnearestintegerbasedbinarybatalgorithmforprediction AT harudinnolia taguchistmethodwithnearestintegerbasedbinarybatalgorithmforprediction |