Related references
Note: Only part of the references are listed.Building energy consumption prediction for residential buildings using deep learning and other machine learning techniques
Razak Olu-Ajayi et al.
JOURNAL OF BUILDING ENGINEERING (2022)
Machine learning for early stage building energy prediction: Increment and enrichment
Manav Mahan Singh et al.
APPLIED ENERGY (2021)
A building energy consumption prediction model based on rough set theory and deep learning algorithms
Lei Lei et al.
ENERGY AND BUILDINGS (2021)
Towards developing a systematic knowledge trend for building energy consumption prediction
Qingyao Qiao et al.
JOURNAL OF BUILDING ENGINEERING (2021)
Building energy performance assessment using linked data and cross-domain semantic reasoning
Shushan Hu et al.
AUTOMATION IN CONSTRUCTION (2021)
Machine learning for occupant-behavior-sensitive cooling energy consumption prediction in office buildings
Kadir Amasyali et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)
Heating and cooling energy consumption prediction model for high-rise apartment buildings considering design parameters
Daeung Danny Kim et al.
ENERGY FOR SUSTAINABLE DEVELOPMENT (2021)
Hourly energy consumption prediction of an office building based on ensemble learning and energy consumption pattern classification
Zhenxiang Dong et al.
ENERGY AND BUILDINGS (2021)
Energy consumption prediction by using machine learning for smart building: Case study in Malaysia
Mel Keytingan M. Shapi et al.
DEVELOPMENTS IN THE BUILT ENVIRONMENT (2021)
A novel improved model for building energy consumption prediction based on model integration
Ran Wang et al.
APPLIED ENERGY (2020)
A comparative analysis of data-driven methods in building energy benchmarking
Yong Ding et al.
ENERGY AND BUILDINGS (2020)
Data driven model improved by multi-objective optimisation for prediction of building energy loads
Saleh Seyedzadeh et al.
AUTOMATION IN CONSTRUCTION (2020)
Deep learning techniques for energy forecasting and condition monitoring in the manufacturing sector
Victoria Jayne Mawson et al.
ENERGY AND BUILDINGS (2020)
Predicting energy consumption in multiple buildings using machine learning for improving energy efficiency and sustainability
Anh-Duc Pham et al.
JOURNAL OF CLEANER PRODUCTION (2020)
A machine learning algorithm to improve building performance modeling during design
Chanachok Chokwitthaya et al.
METHODSX (2020)
Energy consumption prediction and diagnosis of public buildings based on support vector machine learning: A case study in China
Yang Liu et al.
JOURNAL OF CLEANER PRODUCTION (2020)
Machine learning applications in urban building energy performance forecasting: A systematic review
Soheil Fathi et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2020)
Building power consumption datasets: Survey, taxonomy and future directions
Yassine Himeur et al.
ENERGY AND BUILDINGS (2020)
The effect of wall material on energy cost reduction in building
Marwan Marwan
CASE STUDIES IN THERMAL ENGINEERING (2020)
Feature selection using an improved Chi-square for Arabic text classification
Said Bahassine et al.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES (2020)
A Big Data Analytics Approach for Construction Firms Failure Prediction Models
Hafiz Alaka et al.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT (2019)
Vector field-based support vector regression for building energy consumption prediction
Hai Zhong et al.
APPLIED ENERGY (2019)
A Scalable Hierarchical Gaussian Process Classifier
Thi Nhat Anh Nguyen et al.
IEEE TRANSACTIONS ON SIGNAL PROCESSING (2019)
Gradient Boosted Trees Predictive Models for Surface Roughness in High-Speed Milling in the Steel and Aluminum Metalworking Industry
Victor Flores et al.
COMPLEXITY (2019)
Modeling and forecasting building energy consumption: A review of data-driven techniques
Mathieu Bourdeau et al.
SUSTAINABLE CITIES AND SOCIETY (2019)
Forecasting Energy Use in Buildings Using Artificial Neural Networks: A Review
Jason Runge et al.
ENERGIES (2019)
A systematic feature selection procedure for short-term data-driven building energy forecasting model development
Liang Zhang et al.
ENERGY AND BUILDINGS (2019)
Short-term load forecasting using machine learning and periodicity decomposition
Abdelkarim El Khantach et al.
AIMS ENERGY (2019)
Random Forest based hourly building energy prediction
Zeyu Wang et al.
ENERGY AND BUILDINGS (2018)
A novel ensemble learning approach to support building energy use prediction
Zeyu Wang et al.
ENERGY AND BUILDINGS (2018)
A hybrid teaching-learning artificial neural network for building electrical energy consumption prediction
Kangji Li et al.
ENERGY AND BUILDINGS (2018)
Systematic review of bankruptcy prediction models: Towards a framework for tool selection
Hafiz A. Alaka et al.
EXPERT SYSTEMS WITH APPLICATIONS (2018)
A system dynamics-based environmental benefit assessment model of construction waste reduction management at the design and construction stages
Zhikun Ding et al.
JOURNAL OF CLEANER PRODUCTION (2018)
A review of data-driven building energy consumption prediction studies
Kadir Amasyali et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2018)
Building energy savings: Analysis of research trends based on text mining
Zhikun Ding et al.
AUTOMATION IN CONSTRUCTION (2018)
Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption
Muhammad Waseem Ahmad et al.
ENERGY AND BUILDINGS (2017)
A review on time series forecasting techniques for building energy consumption
Chirag Deb et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2017)
Does window-to-wall ratio have a significant effect on the energy consumption of buildings? A parametric analysis in Italian climate conditions
C. Marino et al.
JOURNAL OF BUILDING ENGINEERING (2017)
Machine learning approaches for estimating commercial building energy consumption
Caleb Robinson et al.
APPLIED ENERGY (2017)
Intrusion detection model using fusion of chi-square feature selection and multi class SVM
Sumaiya Thaseen Ikram et al.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES (2017)
Visualized strategy for predicting buildings energy consumption during early design stage using parametric analysis
Emad Elbeltagi et al.
JOURNAL OF BUILDING ENGINEERING (2017)
Gradient boosting for high-dimensional prediction of rare events
Rok Blagus et al.
COMPUTATIONAL STATISTICS & DATA ANALYSIS (2017)
Artificial neural network model for forecasting sub-hourly electricity usage in commercial buildings
Young Tae Chae et al.
ENERGY AND BUILDINGS (2016)
Prediction of energy performance of residential buildings: A genetic programming approach
Mauro Castelli et al.
ENERGY AND BUILDINGS (2015)
Active Learning With Gaussian Process Classifier for Hyperspectral Image Classification
Shujin Sun et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2015)
Missing Data How to Best Account for What Is Not Known
Craig D. Newgard et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2015)
Data driven approaches for prediction of building energy consumption at urban level
Giovanni Tardioli et al.
6TH INTERNATIONAL BUILDING PHYSICS CONFERENCE (IBPC 2015) (2015)
Impact of urban form on energy use in central city and suburban neighborhoods: Lessons from the Phoenix metropolitan region
Subhrajit Guhathakurta et al.
CLEAN, EFFICIENT AND AFFORDABLE ENERGY FOR A SUSTAINABLE FUTURE (2015)
GSVM: An SVM for handling imbalanced accuracy between classes inbi-classification problems
L. Gonzalez-Abril et al.
APPLIED SOFT COMPUTING (2014)
Modeling heating and cooling loads by artificial intelligence for energy-efficient building design
Jui-Sheng Chou et al.
ENERGY AND BUILDINGS (2014)
A review of microarray datasets and applied feature selection methods
V. Bolon-Canedo et al.
INFORMATION SCIENCES (2014)
Review of building energy modeling for control and operation
Xiwang Li et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2014)
A review on applications of ANN and SVM for building electrical energy consumption forecasting
A. S. Ahmad et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2014)
Critical factors in effective construction waste minimization at the design stage: A Shenzhen case study, China
Jiayuan Wang et al.
RESOURCES CONSERVATION AND RECYCLING (2014)
Solutions to reduce energy consumption in the management of large buildings
Antonio Colmenar-Santos et al.
ENERGY AND BUILDINGS (2013)
A Few Useful Things to Know About Machine Learning
Pedro Domingos
COMMUNICATIONS OF THE ACM (2012)
A review on the prediction of building energy consumption
Hai-xiang Zhao et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2012)
Optimum, technical and energy efficiency design of residential building in Mediterranean region
Samar Jaber et al.
ENERGY AND BUILDINGS (2011)
Classification and regression trees
Wei-Yin Loh
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY (2011)
Assessment of the variation impacts of window on energy consumption and carbon footprint
Mohammad Mahdi Tahmasebi et al.
2011 INTERNATIONAL CONFERENCE ON GREEN BUILDINGS AND SUSTAINABLE CITIES (2011)
A data-driven approach for steam load prediction in buildings
Andrew Kusiak et al.
APPLIED ENERGY (2010)
Artificial neural networks for energy analysis of office buildings with daylighting
S. L. Wong et al.
APPLIED ENERGY (2010)
A decision tree method for building energy demand modeling
Zhun Yu et al.
ENERGY AND BUILDINGS (2010)
Impacts of urban form on future US passenger-vehicle greenhouse gas emissions
Steve Hankey et al.
ENERGY POLICY (2010)
Power load forecasting using support vector machine and ant colony optimization
Dongxiao Niu et al.
EXPERT SYSTEMS WITH APPLICATIONS (2010)
Applying support vector machine to predict hourly cooling load in the building
Qiong Li et al.
APPLIED ENERGY (2009)
Predicting hourly cooling load in the building: A comparison of support vector machine and different artificial neural networks
Qiong Li et al.
ENERGY CONVERSION AND MANAGEMENT (2009)
Contrasting the capabilities of building energy performance simulation programs
Drury B. Crawley et al.
BUILDING AND ENVIRONMENT (2008)
Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption
Alberto Hernandez Neto et al.
ENERGY AND BUILDINGS (2008)
An applied artificial intelligence approach towards assessing building performance simulation tools
Abraham Yezioro et al.
ENERGY AND BUILDINGS (2008)
Vapnik's learning theory applied to energy consumption forecasts in residential buildings
Florence Lai et al.
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS (2008)
Predicting electricity energy consumption: A comparison of regression analysis, decision tree and neural networks
Geoffrey K. F. Tso et al.
ENERGY (2007)
Applying computer-based simulation to energy auditing: A case study
YM Zhu
ENERGY AND BUILDINGS (2006)
Applying multi-objective genetic algorithms in green building design optimization
WM Wang et al.
BUILDING AND ENVIRONMENT (2005)
Applying support vector machines to predict building energy consumption in tropical region
B Dong et al.
ENERGY AND BUILDINGS (2005)
An OTTV-based energy estimation model for commercial buildings in Thailand
S Chirarattananon et al.
ENERGY AND BUILDINGS (2004)