Systematic Review of Deep Learning and Machine Learning for Building Energy

Forecasting of water thermal conductivity enhancement by adding nano-sized alumina particles

(2021) Salah I. Yahya et al.   JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY

An artificial intelligence approach to optimization of an off-grid hybrid wind/hydrogen system

(2021) Weiping Zhang et al.   INTERNATIONAL JOURNAL OF HYDROGEN ENERGY

A Pragmatic Investigation of Energy Consumption and Utilization Models in the Urban Sector Using Predictive Intelligence Approaches

(2021) Sunil Kumar Mohapatra et al.   Energies

Trending machine learning models in cyber‐physical building environment: A survey

(2021) Zahid Hasan et al.   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

Artificial intelligence techniques for enabling Big Data services in distribution networks: A review

(2021) Sara Barja-Martinez et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Accurate forecasting of building energy consumption via a novel ensembled deep learning method considering the cyclic feature

(2020) Guiqing Zhang et al.   ENERGY

A hybrid deep learning-based method for short-term building energy load prediction combined with an interpretation process

(2020) Chaobo Zhang et al.   ENERGY AND BUILDINGS

Multi-population differential evolution-assisted Harris hawks optimization: Framework and case studies

(2020) Hao Chen et al.   Future Generation Computer Systems-The International Journal of eScience

Chaotic random spare ant colony optimization for multi-threshold image segmentation of 2D Kapur entropy

(2020) Dong Zhao et al.   KNOWLEDGE-BASED SYSTEMS

Towards Augmented Kernel Extreme Learning Models for Bankruptcy Prediction: Algorithmic Behavior and Comprehensive Analysis

(2020) Yanan Zhang et al.   NEUROCOMPUTING

Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics

(2020) Amirhosein Mosavi et al.   Mathematics

Evolutionary biogeography-based whale optimization methods with communication structure: Towards measuring the balance

(2020) Jiaze Tu et al.   KNOWLEDGE-BASED SYSTEMS

Rooftop Solar PV Penetration Impacts on Distribution Network and Further Growth Factors—A Comprehensive Review

(2020) Busra Uzum et al.   Electronics

Orthogonal learning covariance matrix for defects of grey wolf optimizer: Insights, balance, diversity, and feature selection

(2020) Jiao Hu et al.   KNOWLEDGE-BASED SYSTEMS

Double adaptive weights for stabilization of moth flame optimizer: Balance analysis, engineering cases, and medical diagnosis

(2020) Weifeng Shan et al.   KNOWLEDGE-BASED SYSTEMS

Developing a predictive method based on optimized M5Rules–GA predicting heating load of an energy-efficient building system

(2019) Xuan-Nam Bui et al.   ENGINEERING WITH COMPUTERS

Machine Learning for Smart Building Applications

(2019) Djamel Djenouri et al.   ACM COMPUTING SURVEYS

Data fusion in predicting internal heat gains for office buildings through a deep learning approach

(2019) Zhe Wang et al.   APPLIED ENERGY

Towards an Automated, Fast and Interpretable Estimation Model of Heating Energy Demand: A Data-Driven Approach Exploiting Building Energy Certificates

(2019) Antonio Attanasio et al.   Energies

Prediction model on disturbance of maintenance operation during real‐time pricing adaptive control for building air‐conditioners

(2019) Shun Matsukawa et al.   IEEJ Transactions on Electrical and Electronic Engineering

An ANN-based model for the prediction of internal lighting conditions and user actions in non-residential buildings

(2019) Varvara N. Katsanou et al.   Journal of Building Performance Simulation

Data-Driven Building Load Profiling and Energy Management

(2019) Jin Zhu et al.   Sustainable Cities and Society

Tuning machine learning models for prediction of building energy loads

(2019) Saleh Seyedzadeh et al.   Sustainable Cities and Society

An efficient data model for energy prediction using wireless sensors

(2019) Michel Chammas et al.   COMPUTERS & ELECTRICAL ENGINEERING

Toward efficient energy systems based on natural gas consumption prediction with LSTM Recurrent Neural Networks

(2019) Oussama Laib et al.   ENERGY

Economic model predictive control for demand flexibility of a residential building

(2019) Christian Finck et al.   ENERGY

Comparative study of data driven methods in building electricity use prediction

(2019) Aaron Zeng et al.   ENERGY AND BUILDINGS

Recurrent inception convolution neural network for multi short-term load forecasting

(2019) Junhong Kim et al.   ENERGY AND BUILDINGS

Prediction and analysis of heating energy demand for detached houses by computer vision

(2019) Miroslav Despotovic et al.   ENERGY AND BUILDINGS

A Modified Fuzzy Logic Relation-Based Approach for Electricity Consumption Forecasting in India

(2019) Rachna Jain et al.   International Journal of Fuzzy Systems

A Comparative Study of PSO-ANN, GA-ANN, ICA-ANN, and ABC-ANN in Estimating the Heating Load of Buildings’ Energy Efficiency for Smart City Planning

(2019) Le Thi Le et al.   Applied Sciences-Basel

Development of an IoT-based big data platform for day-ahead prediction of building heating and cooling demands

(2019) X.J. Luo et al.   ADVANCED ENGINEERING INFORMATICS

Predicting plug loads with occupant count data through a deep learning approach

(2019) Zhe Wang et al.   ENERGY

Predictive modelling of building energy consumption based on a hybrid nature-inspired optimization algorithm

(2019) Shidrokh Goudarzi et al.   ENERGY AND BUILDINGS

Developing surrogate ANN for selecting near-optimal building energy renovation methods considering energy consumption, LCC and LCA

(2019) Seyed Amirhosain Sharif et al.   Journal of Building Engineering

A hybrid hierarchical soft computing approach for the technology selection problem in brick industry considering environmental competencies: A case study

(2019) Ehsan Solgi et al.   JOURNAL OF ENVIRONMENTAL MANAGEMENT

Deep-learning neural-network architectures and methods: Using component-based models in building-design energy prediction

(2018) Sundaravelpandian Singaravel et al.   ADVANCED ENGINEERING INFORMATICS

Predicting electricity consumption for commercial and residential buildings using deep recurrent neural networks

(2018) Aowabin Rahman et al.   APPLIED ENERGY

Predicting heating demand and sizing a stratified thermal storage tank using deep learning algorithms

(2018) Aowabin Rahman et al.   APPLIED ENERGY

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

A review of data-driven building energy consumption prediction studies

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

Data-driven heating and cooling load predictions for non-residential buildings based on support vector machine regression and NARX Recurrent Neural Network: A comparative study on district scale

(2018) D. Koschwitz et al.   ENERGY

Forecasting Energy Consumption Time Series using Machine Learning Techniques based on Usage Patterns of Residential Householders

(2018) Jui-Sheng Chou et al.   ENERGY

Towards occupant activity driven smart buildings via WiFi-enabled IoT devices and deep learning

(2018) Han Zou et al.   ENERGY AND BUILDINGS

A comparison of models for forecasting the residential natural gas demand of an urban area

(2018) Rok Hribar et al.   ENERGY

Early predicting cooling loads for energy-efficient design in office buildings by machine learning

(2018) Ngoc-Tri Ngo   ENERGY AND BUILDINGS

Fusing TensorFlow with building energy simulation for intelligent energy management in smart cities

(2018) José R. Vázquez-Canteli et al.   Sustainable Cities and Society

Deployment of data-mining short and medium-term horizon cooling load forecasting models for building energy optimization and management

(2018) Tanveer Ahmad et al.   INTERNATIONAL JOURNAL OF REFRIGERATION-REVUE INTERNATIONALE DU FROID

Parallel memetic algorithm for training recurrent neural networks for the energy efficiency problem

(2018) L.G.B. Ruiz et al.   APPLIED SOFT COMPUTING

Assessment of deep recurrent neural network-based strategies for short-term building energy predictions

(2018) Cheng Fan et al.   APPLIED ENERGY

Day-ahead building-level load forecasts using deep learning vs. traditional time-series techniques

(2018) Mengmeng Cai et al.   APPLIED ENERGY

A novel data-driven approach for transient stability prediction of power systems considering the operational variability

(2018) Yanzhen Zhou et al.   INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

A Smart Forecasting Approach to District Energy Management

(2017) Baris Yuce et al.   Energies

Comparison of Different Solar-Assisted Air Conditioning Systems for Australian Office Buildings

(2017) Yunlong Ma et al.   Energies

Building Energy Consumption Prediction: An Extreme Deep Learning Approach

(2017) Chengdong Li et al.   Energies

Building Applications, Opportunities and Challenges of Active Shading Systems: A State-of-the-Art Review

(2017) Joud Al Dakheel et al.   Energies

Predicting the energy demand of buildings during triad peaks in GB

(2017) Charalampos Marmaras et al.   ENERGY AND BUILDINGS

Evaluation of tree-based ensemble learning algorithms for building energy performance estimation

(2017) Sokratis Papadopoulos et al.   Journal of Building Performance Simulation

Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns

(2016) Jui-Sheng Chou et al.   APPLIED ENERGY

Forecasting diurnal cooling energy load for institutional buildings using Artificial Neural Networks

(2016) Chirag Deb et al.   ENERGY AND BUILDINGS

Comparative analysis and assessment of ANFIS-based domestic lighting profile modelling

(2015) O. Popoola et al.   ENERGY AND BUILDINGS

Building Behavior Simulation by Means of Artificial Neural Network in Summer Conditions

(2014) Cinzia Buratti et al.   Sustainability