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Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/24350Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Li, Z | - |
| dc.contributor.author | Lai, CS | - |
| dc.contributor.author | Meng, A | - |
| dc.contributor.author | Li, X | - |
| dc.contributor.author | Vaccaro, A | - |
| dc.contributor.author | Lai, LL | - |
| dc.date.accessioned | 2022-03-28T08:42:21Z | - |
| dc.date.available | 2022-03-28T08:42:21Z | - |
| dc.date.issued | 2021-12-04 | - |
| dc.identifier.citation | Li, Z., Lai, C.S., Meng, A., Li, X., Vaccaro, A. and Lai, L.L. (2022) 'Artificial Intelligent Techniques for Solar Energy Generation & Household Load Forecasting', 2021 International Conference on Machine Learning and Cybernetics (ICMLC), Adelaide, Australia (virtual), 4-5 December, pp. 1-4. doi: 10.1109/ICMLC54886.2021.9737261. | en_US |
| dc.identifier.isbn | 978-1-6654-6608-0 | - |
| dc.identifier.isbn | 978-1-6654-6609-7 | - |
| dc.identifier.issn | 2160-133X | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/24350 | - |
| dc.description.sponsorship | Education Department of Guangdong Province: New and Integrated Energy System Theory and Technology Research Group [Project Number 2016KCXTD022]; Brunei University London BRIEF Funding, UK. | en_US |
| dc.format.extent | 1 - 4 | - |
| dc.format.medium | Print-Electronic | - |
| dc.language.iso | en_US | en_US |
| dc.publisher | IEEE | en_US |
| dc.rights | Copyright © 2021 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. | - |
| dc.source | 2021 International Conference on Machine Learning and Cybernetics (ICMLC) | - |
| dc.source | 2021 International Conference on Machine Learning and Cybernetics (ICMLC) | - |
| dc.subject | machine learning | en_US |
| dc.subject | solar energy | en_US |
| dc.subject | household load | en_US |
| dc.title | Artificial Intelligent Techniques for Solar Energy Generation & Household Load Forecasting | en_US |
| dc.type | Conference Paper | en_US |
| dc.identifier.doi | https://doi.org/10.1109/icmlc54886.2021.9737261 | - |
| dc.relation.isPartOf | 2021 International Conference on Machine Learning and Cybernetics (ICMLC) | - |
| pubs.finish-date | 2021-12-05 | - |
| pubs.finish-date | 2021-12-05 | - |
| pubs.publication-status | Published | - |
| pubs.start-date | 2021-12-04 | - |
| pubs.start-date | 2021-12-04 | - |
| dc.identifier.eissn | 2160-1348 | - |
| Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Copyright © 2021 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. | 2.59 MB | Adobe PDF | View/Open |
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