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DC Field | Value | Language |
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dc.contributor.author | Li, H | - |
dc.contributor.author | Wang, Z | - |
dc.contributor.author | Lan, C | - |
dc.contributor.author | Wu, P | - |
dc.contributor.author | Zeng, N | - |
dc.date.accessioned | 2023-08-31T18:37:46Z | - |
dc.date.available | 2023-08-31T18:37:46Z | - |
dc.date.issued | 2023-07-28 | - |
dc.identifier | ORCID iDs: Han Li https://orcid.org/0000-0003-0276-9756; Zidong Wang https://orcid.org/0000-0002-9576-7401; Peishu Wu https://orcid.org/0000-0001-9891-3809; Nianyin Zeng https://orcid.org/0000-0002-6957-2942. | - |
dc.identifier.citation | Li, H. et al. (2023) 'A Novel Dynamic Multiobjective Optimization Algorithm With Non-Inductive Transfer Learning Based on Multi-Strategy Adaptive Selection', IEEE Transactions on Neural Networks and Learning Systems, 0 (early access), pp. 1 - 15. doi: 10.1109/tnnls.2023.3295461. | en_US |
dc.identifier.issn | 2162-237X | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/27099 | - |
dc.description.sponsorship | Natural Science Foundation of China (Grant Number: 61933007 and 62073271); National Science and Technology Major Project of China (Grant Number: J2019-I-0013-0013); Independent Innovation Foundation of Aero Engine Corporation of China (AECC) of China (Grant Number: ZZCX-2018-017); 10.13039/501100007633-Korea Foundation for Advanced Studies; Natural Science Foundation for Distinguished Young Scholars of Fujian Province of China (Grant Number: 2023J06010). | en_US |
dc.format.extent | 1 - 15 | - |
dc.format.medium | Print-Electronic | - |
dc.language | English | - |
dc.language.iso | en_US | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.rights | Copyright © 2023 Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works by sending a request to pubs-permissions@ieee.org. For more information, see https://www.ieee.org/publications/rights/rights-policies.html | - |
dc.rights.uri | https://www.ieee.org/publications/rights/rights-policies.html | - |
dc.subject | dynamic multiobjective optimization algorithm (DMOA) | en_US |
dc.subject | evolutionary transfer optimization (ETO) | en_US |
dc.subject | kernel mean matching (KMM) | en_US |
dc.subject | transfer learning (TL) | en_US |
dc.title | A Novel Dynamic Multiobjective Optimization Algorithm With Non-Inductive Transfer Learning Based on Multi-Strategy Adaptive Selection | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.1109/tnnls.2023.3295461 | - |
dc.relation.isPartOf | IEEE Transactions on Neural Networks and Learning Systems | - |
pubs.issue | Early Access | - |
pubs.publication-status | Published | - |
pubs.volume | 0 | - |
dc.identifier.eissn | 2162-2388 | - |
dc.rights.holder | Institute of Electrical and Electronics Engineers (IEEE) | - |
Appears in Collections: | Dept of Computer Science Research Papers |
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FullText.pdf | Copyright © 2023 Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works by sending a request to pubs-permissions@ieee.org. For more information, see https://www.ieee.org/publications/rights/rights-policies.html | 2.4 MB | Adobe PDF | View/Open |
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