Investigating the performance of machine learning models combined with different feature selection methods to estimate the energy consumption of buildings
出版年份 2022 全文链接
标题
Investigating the performance of machine learning models combined with different feature selection methods to estimate the energy consumption of buildings
作者
关键词
-
出版物
ENERGY AND BUILDINGS
Volume 273, Issue -, Pages 112408
出版商
Elsevier BV
发表日期
2022-08-19
DOI
10.1016/j.enbuild.2022.112408
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- BEEM: Data-driven building energy benchmarking for Singapore
- (2022) Pandarasamy Arjunan et al. ENERGY AND BUILDINGS
- GEIN: An interpretable benchmarking framework towards all building types based on machine learning
- (2022) Xiaoyu Jin et al. ENERGY AND BUILDINGS
- Challenges and opportunities for carbon neutrality in China’s building sector—Modelling and data
- (2022) Shan Hu et al. Building Simulation
- Examining the feasibility of using open data to benchmark building energy usage in cities: A data science and policy perspective
- (2020) Jonathan Roth et al. ENERGY POLICY
- Energy characteristics of urban buildings: Assessment by machine learning
- (2020) Wei Tian et al. Building Simulation
- A review of operational energy consumption calculation method for urban buildings
- (2020) Ziwei Li et al. Building Simulation
- Data-driven estimation of building energy consumption with multi-source heterogeneous data
- (2020) Yue Pan et al. APPLIED ENERGY
- EnergyStar++: Towards more accurate and explanatory building energy benchmarking
- (2020) Pandarasamy Arjunan et al. APPLIED ENERGY
- Energy prediction techniques for large-scale buildings towards a sustainable built environment: A review
- (2020) Abdo Abdullah Ahmed Gassar et al. ENERGY AND BUILDINGS
- Energy and carbon performance of urban buildings using metamodeling variable importance techniques
- (2020) Yunliang Liu et al. Building Simulation
- An ANN-based fast building energy consumption prediction method for complex architectural form at the early design stage
- (2019) Ziwei Li et al. Building Simulation
- DUE-B: Data-driven urban energy benchmarking of buildings using recursive partitioning and stochastic frontier analysis
- (2018) Zheng Yang et al. ENERGY AND BUILDINGS
- Predictive modeling for US commercial building energy use: A comparison of existing statistical and machine learning algorithms using CBECS microdata
- (2018) Hengfang Deng et al. ENERGY AND BUILDINGS
- A review of data-driven approaches for prediction and classification of building energy consumption
- (2018) Yixuan Wei et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Modeling occupancy and behavior for better building design and operation—A critical review
- (2018) Bing Dong et al. Building Simulation
- On the feature engineering of building energy data mining
- (2018) Chuan Zhang et al. Sustainable Cities and Society
- Benchmarking energy performance for cooling in large commercial buildings
- (2018) Haoru Li et al. ENERGY AND BUILDINGS
- Grading buildings on energy performance using city benchmarking data
- (2018) Sokratis Papadopoulos et al. APPLIED ENERGY
- Estimating energy savings from benchmarking policies in New York City
- (2017) Ting Meng et al. ENERGY
- Comparison of linear regression and artificial neural networks models to predict heating and cooling energy demand, energy consumption and CO 2 emissions
- (2017) Rafael Pino-Mejías et al. ENERGY
- IEA EBC annex 53: Total energy use in buildings—Analysis and evaluation methods
- (2017) Hiroshi Yoshino et al. ENERGY AND BUILDINGS
- A review of artificial intelligence based building energy use prediction: Contrasting the capabilities of single and ensemble prediction models
- (2017) Zeyu Wang et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Estimation of the building energy use intensity in the urban scale by integrating GIS and big data technology
- (2016) Jun Ma et al. APPLIED ENERGY
- Identifying the influential features on the regional energy use intensity of residential buildings based on Random Forests
- (2016) Jun Ma et al. APPLIED ENERGY
- A regression-based approach to estimating retrofit savings using the Building Performance Database
- (2016) Travis Walter et al. APPLIED ENERGY
- A study on the energy performance of school buildings in Taiwan
- (2016) Jen Chun Wang ENERGY AND BUILDINGS
- Regularization Paths for Generalized Linear Models via Coordinate Descent
- (2015) Jerome Friedman et al. Journal of Statistical Software
- Developing energy consumption benchmarks for buildings: Bank branches in Brazil
- (2014) Edward H. Borgstein et al. ENERGY AND BUILDINGS
- A new methodology for building energy performance benchmarking: An approach based on intelligent clustering algorithm
- (2014) Xuefeng Gao et al. ENERGY AND BUILDINGS
- Mutual Information between Discrete and Continuous Data Sets
- (2014) Brian C. Ross PLoS One
- A review on simulation-based optimization methods applied to building performance analysis
- (2013) Anh-Tuan Nguyen et al. APPLIED ENERGY
- Regression shrinkage and selection via the lasso: a retrospective
- (2011) Robert Tibshirani JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
- Benchmarking energy use and greenhouse gas emissions in Singapore’s hotel industry
- (2010) Wu Xuchao et al. ENERGY POLICY
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now