A machine-learning-based approach to predict residential annual space heating and cooling loads considering occupant behaviour

I-BLEND, a campus-scale commercial and residential buildings electrical energy dataset

(2019) Haroon Rashid et al.   Scientific Data

Low carbon heating and cooling of residential buildings in cities in the hot summer and cold winter zone - A bottom-up engineering stock modeling approach

(2019) Xinyi Li et al.   JOURNAL OF CLEANER PRODUCTION

The Impact of Building Occupant Behavior on Energy Efficiency and Methods to Influence It: A Review of the State of the Art

(2018) Antonio Paone et al.   Energies

A comprehensive overview on the data driven and large scale based approaches for forecasting of building energy demand: A review

(2018) Tanveer Ahmad et al.   ENERGY AND BUILDINGS

The suitability of machine learning to minimise uncertainty in the measurement and verification of energy savings

(2018) Colm V. Gallagher 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

Adaptive learning based data-driven models for predicting hourly building energy use

(2018) Liping Wang et al.   ENERGY AND BUILDINGS

A review on occupant behavior in urban building energy models

(2018) Gabriel Happle 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

A review of data-driven building energy consumption prediction studies

(2018) Kadir Amasyali et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

A review on optimization methods applied in energy-efficient building geometry and envelope design

(2018) Farshad Kheiri   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

A survey on energy consumption and energy usage behavior of households and residential building in urban China

(2017) Shan Hu et al.   ENERGY AND BUILDINGS

A relevant data selection method for energy consumption prediction of low energy building based on support vector machine

(2017) Subodh Paudel et al.   ENERGY AND BUILDINGS

The impact of occupants’ behaviours on building energy analysis: A research review

(2017) Elham Delzendeh et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

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

Estimating building energy consumption using extreme learning machine method

(2016) Sareh Naji et al.   ENERGY

Time series forecasting for building energy consumption using weighted Support Vector Regression with differential evolution optimization technique

(2016) Fan Zhang et al.   ENERGY AND BUILDINGS

Advances in research and applications of energy-related occupant behavior in buildings

(2016) Tianzhen Hong et al.   ENERGY AND BUILDINGS

The effect of building envelope on the thermal comfort and energy saving for high-rise buildings in hot–humid climate

(2016) Seyedehzahra Mirrahimi et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Residential heating energy consumption modeling through a bottom-up approach for China's Hot Summer–Cold Winter climatic region

(2015) Zhe Wang et al.   ENERGY AND BUILDINGS

Short-term load forecasting in a non-residential building contrasting models and attributes

(2015) Joaquim Massana et al.   ENERGY AND BUILDINGS

Prediction of building energy consumption using an improved real coded genetic algorithm based least squares support vector machine approach

(2015) Hyun Chul Jung et al.   ENERGY AND BUILDINGS

Cross-validation for selecting a model selection procedure

(2015) Yongli Zhang et al.   JOURNAL OF ECONOMETRICS

Improving the energy performance of residential buildings: A literature review

(2015) L. De Boeck et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Forecasting energy consumption of multi-family residential buildings using support vector regression: Investigating the impact of temporal and spatial monitoring granularity on performance accuracy

(2014) Rishee K. Jain et al.   APPLIED ENERGY

Modeling heating and cooling loads by artificial intelligence for energy-efficient building design

(2014) Jui-Sheng Chou et al.   ENERGY AND BUILDINGS

Comparative study of a building energy performance software (KEP-IYTE-ESS) and ANN-based building heat load estimation

(2014) Cihan Turhan et al.   ENERGY AND BUILDINGS

A new calculation method for shape coefficient of residential building using Google Earth

(2014) Feng Qi et al.   ENERGY AND BUILDINGS

Characteristics of residential energy consumption in China: Findings from a household survey

(2014) Xinye Zheng et al.   ENERGY POLICY

A review of methods to match building energy simulation models to measured data

(2014) Daniel Coakley et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

State of the art in building modelling and energy performances prediction: A review

(2013) Aurélie Foucquier et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Building hourly thermal load prediction using an indexed ARX model

(2012) Kyungtae Yun et al.   ENERGY AND BUILDINGS

Accurate quantitative estimation of energy performance of residential buildings using statistical machine learning tools

(2012) Athanasios Tsanas et al.   ENERGY AND BUILDINGS

Predicting future hourly residential electrical consumption: A machine learning case study

(2012) Richard E. Edwards et al.   ENERGY AND BUILDINGS

Multiple regression model for fast prediction of the heating energy demand

(2012) Tiberiu Catalina et al.   ENERGY AND BUILDINGS

A review on the prediction of building energy consumption

(2012) Hai-xiang Zhao et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Applying support vector machine to predict hourly cooling load in the building

(2009) Qiong Li et al.   APPLIED ENERGY

Predicting hourly cooling load in the building: A comparison of support vector machine and different artificial neural networks

(2008) Qiong Li et al.   ENERGY CONVERSION AND MANAGEMENT

Vapnik's learning theory applied to energy consumption forecasts in residential buildings

(2008) Florence Lai et al.   INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS