Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA)
This paper sets pioneering research which investigates the parametric identification of thermoelectric modules (TEMs) through the employment of enhanced slime mould algorithm (ESMA). The proposed method incorporates a pair of modifications to the standard slime mould algorithm (SMA). Primary modific...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier B.V.
2024
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| Online Access: | http://umpir.ump.edu.my/id/eprint/42792/ http://umpir.ump.edu.my/id/eprint/42792/1/Parameter%20identification%20of%20thermoelectric%20modules%20using%20enhanced%20slime%20mould%20algorithm.pdf |
| _version_ | 1848826703050178560 |
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| author | Ponnalagu, Dharswini Mohd Ashraf, Ahmad Jui, Julakha Jahan |
| author_facet | Ponnalagu, Dharswini Mohd Ashraf, Ahmad Jui, Julakha Jahan |
| author_sort | Ponnalagu, Dharswini |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | This paper sets pioneering research which investigates the parametric identification of thermoelectric modules (TEMs) through the employment of enhanced slime mould algorithm (ESMA). The proposed method incorporates a pair of modifications to the standard slime mould algorithm (SMA). Primary modification encloses computation of random average position between the slimes' current individual position and best individual position towards resolution of local optima issue. Subsequent modification then involves substitution of an exponential function to the existing tangent hyperbolic function within formula p of the standard SMA in enabling improved probability variants via the selection of updated equations. Competency of the proposed algorithm in generating the optimal parameters for TEMs was appraised based on 21 benchmarked design parameters, following the objective of root mean square error (RMSE) minimization between the temperature of both actual and estimated models. Acquired results which demonstrate lower values of RMSE and parameter deviation index against the standard SMA and other preceding algorithms such as particle swarm optimization, sine cosine algorithm, moth flame optimizer and ant lion optimizer ultimately verified ESMA’s efficacy as an effective approach for accurate model identification. |
| first_indexed | 2025-11-15T03:49:02Z |
| format | Article |
| id | ump-42792 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:49:02Z |
| publishDate | 2024 |
| publisher | Elsevier B.V. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-427922024-10-18T03:42:01Z http://umpir.ump.edu.my/id/eprint/42792/ Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) Ponnalagu, Dharswini Mohd Ashraf, Ahmad Jui, Julakha Jahan TK Electrical engineering. Electronics Nuclear engineering This paper sets pioneering research which investigates the parametric identification of thermoelectric modules (TEMs) through the employment of enhanced slime mould algorithm (ESMA). The proposed method incorporates a pair of modifications to the standard slime mould algorithm (SMA). Primary modification encloses computation of random average position between the slimes' current individual position and best individual position towards resolution of local optima issue. Subsequent modification then involves substitution of an exponential function to the existing tangent hyperbolic function within formula p of the standard SMA in enabling improved probability variants via the selection of updated equations. Competency of the proposed algorithm in generating the optimal parameters for TEMs was appraised based on 21 benchmarked design parameters, following the objective of root mean square error (RMSE) minimization between the temperature of both actual and estimated models. Acquired results which demonstrate lower values of RMSE and parameter deviation index against the standard SMA and other preceding algorithms such as particle swarm optimization, sine cosine algorithm, moth flame optimizer and ant lion optimizer ultimately verified ESMA’s efficacy as an effective approach for accurate model identification. Elsevier B.V. 2024-09-03 Article PeerReviewed pdf en cc_by_nc_nd_4 http://umpir.ump.edu.my/id/eprint/42792/1/Parameter%20identification%20of%20thermoelectric%20modules%20using%20enhanced%20slime%20mould%20algorithm.pdf Ponnalagu, Dharswini and Mohd Ashraf, Ahmad and Jui, Julakha Jahan (2024) Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA). Results in Engineering, 23 (102833). pp. 1-10. ISSN 2590-1230. (Published) https://doi.org/10.1016/j.rineng.2024.102833 https://doi.org/10.1016/j.rineng.2024.102833 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Ponnalagu, Dharswini Mohd Ashraf, Ahmad Jui, Julakha Jahan Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) |
| title | Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) |
| title_full | Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) |
| title_fullStr | Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) |
| title_full_unstemmed | Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) |
| title_short | Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) |
| title_sort | parameter identification of thermoelectric modules using enhanced slime mould algorithm (esma) |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/42792/ http://umpir.ump.edu.my/id/eprint/42792/ http://umpir.ump.edu.my/id/eprint/42792/ http://umpir.ump.edu.my/id/eprint/42792/1/Parameter%20identification%20of%20thermoelectric%20modules%20using%20enhanced%20slime%20mould%20algorithm.pdf |