Generalized building energy and carbon emissions benchmarking with post-prediction analysis-Reference-Cited by-同舟云学术

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Generalized building energy and carbon emissions benchmarking with post-prediction analysis

Published:2024-03 Issue: Volume:17 Page:100320
ISSN:2666-1659
Container-title:Developments in the Built Environment
language:en
Short-container-title:Developments in the Built Environment

Author:

Li Tian^ORCID,Liu Tianqi,Sawyer Azadeh Omidfar,Tang Pingbo,Loftness Vivian,Lu Yi,Xie Jiarong

Funder

Carnegie Mellon University

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Materials Science (miscellaneous),Building and Construction,Civil and Structural Engineering,Architecture

Reference60 articles.

1. An insider data leakage detection using one-hot encoding, synthetic minority oversampling and machine learning techniques;Al-Shehari;Entropy,2021

2. A review of data-driven building energy consumption prediction studies;Amasyali;Renew. Sustain. Energy Rev.,2018

3. EnergyStar++: towards more accurate and explanatory building energy benchmarking;Arjunan;Appl. Energy,2020

4. BEEM: data-driven building energy benchmarking for Singapore;Arjunan;Energy Build.,2022

5. ANSI/ASHRAE/IES Standard 90.1-2019 – Energy Standard for Buildings except Low-Rise Residential Buildings,2019

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MEBA: AI-powered precise building monthly energy benchmarking approach;Applied Energy;2024-04

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