Academic Journal
Identifying critical building-oriented features in city-block-level building energy consumption : a data-driven machine learning approach
| العنوان: | Identifying critical building-oriented features in city-block-level building energy consumption : a data-driven machine learning approach |
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| المؤلفون: | Ye, Z, Cheng, K, Hsu, SC, Wei, HH, Cheung, CM |
| المساهمون: | Department of Civil and Environmental Engineering, Department of Building and Real Estate |
| بيانات النشر: | Pergamon Press |
| سنة النشر: | 2023 |
| المجموعة: | Hong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR) |
| مصطلحات موضوعية: | Building energy modeling, Building-oriented features, City-block level, Feature importance, Random forest |
| الوصف: | 202203 bcfc ; Accepted Manuscript ; Others ; Guangdong Science and Technology Department ; Published ; Green (AAM) |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 0306-2619 1872-9118 |
| Relation: | http://hdl.handle.net/10397/97350; 301; 2-s2.0-85111495917; 117453; CEE-0098 |
| DOI: | 10.1016/j.apenergy.2021.117453 |
| الاتاحة: | http://hdl.handle.net/10397/97350 https://doi.org/10.1016/j.apenergy.2021.117453 |
| Rights: | © 2021 Elsevier Ltd. All rights reserved. ; © 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. ; The following publication Ye, Z., et al. (2021). "Identifying critical building-oriented features in city-block-level building energy consumption: A data-driven machine learning approach." Applied Energy 301: 117453 is available at https://dx.doi.org/10.1016/j.apenergy.2021.117453. |
| رقم الانضمام: | edsbas.96AE1A8E |
| قاعدة البيانات: | BASE |
| تدمد: | 03062619 18729118 |
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| DOI: | 10.1016/j.apenergy.2021.117453 |