A data-driven interval forecasting model for building energy prediction using attention-based LSTM and fuzzy information granulation

Day-ahead probabilistic forecasting for French half-hourly electricity loads and quantiles for curve-to-curve regression

(2021) Xiuqin Xu et al.   APPLIED ENERGY

Early prediction of remaining useful life for Lithium-ion batteries based on a hybrid machine learning method

(2021) Zheming Tong et al.   Journal of Cleaner Production

Model predictive control strategy using encoder-decoder recurrent neural networks for smart control of thermal environment

(2021) Yue Li et al.   Journal of Building Engineering

Prediction of energy consumption in hotel buildings via support vector machines

(2020) Minglei Shao et al.   Sustainable Cities and Society

Machine learning driven smart electric power systems: Current trends and new perspectives

(2020) Muhammad Sohail Ibrahim et al.   APPLIED ENERGY

Sequence-to-sequence neural networks for short-term electrical load forecasting in commercial office buildings

(2020) Elliott Skomski et al.   ENERGY AND BUILDINGS

The short-term interval prediction of wind power using the deep learning model with gradient descend optimization

(2020) Chaoshun Li et al.   RENEWABLE ENERGY

Deep learning and transfer learning models of energy consumption forecasting for a building with poor information data

(2020) Yuan Gao et al.   ENERGY AND BUILDINGS

Comparative study of machine learning-based multi-objective prediction framework for multiple building energy loads

(2020) X.J. Luo et al.   Sustainable Cities and Society

Prediction and optimization of energy consumption in an office building using artificial neural network and a genetic algorithm

(2020) Marjan Ilbeigi et al.   Sustainable Cities and Society

Ensemble empirical mode decomposition and long short-term memory neural network for multi-step predictions of time series signals in nuclear power plants

(2020) Hoang-Phuong Nguyen et al.   APPLIED ENERGY

Tuning machine learning models for prediction of building energy loads

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

Modeling and forecasting building energy consumption: A review of data-driven techniques

(2019) Mathieu Bourdeau et al.   Sustainable Cities and Society

Risk-based probabilistic-possibilistic self-scheduling considering high-impact low-probability events uncertainty

(2019) Hooman Khaloie et al.   INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

A simplified HVAC energy prediction method based on degree-day

(2019) Huajing Sha et al.   Sustainable Cities and Society

Deep ensemble learning based probabilistic load forecasting in smart grids

(2019) Yandong Yang et al.   ENERGY

Pay Attention to the Activations: A Modular Attention Mechanism for Fine-Grained Image Recognition

(2019) Pau Rodriguez et al.   IEEE TRANSACTIONS ON MULTIMEDIA

Wind and solar power probability density prediction via fuzzy information granulation and support vector quantile regression

(2019) Yaoyao He et al.   INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Performance degradation prediction of mechanical equipment based on optimized multi-kernel relevant vector machine and fuzzy information granulation

(2019) Fafa Chen et al.   MEASUREMENT

A method to evaluate building energy consumption based on energy use index of different functional sectors

(2019) Jialin Wu et al.   Sustainable Cities and Society

Short term electricity demand forecasting using partially linear additive quantile regression with an application to the unit commitment problem

(2018) Moshoko Emily Lebotsa et al.   APPLIED ENERGY

Residential probabilistic load forecasting: A method using Gaussian process designed for electric load data

(2018) Mahmoud Shepero et al.   APPLIED ENERGY

Probabilistic forecasting of electricity consumption, photovoltaic power generation and net demand of an individual building using Gaussian Processes

(2018) D.W. van der Meer et al.   APPLIED ENERGY

Parallel and reliable probabilistic load forecasting via quantile regression forest and quantile determination

(2018) Wenjie Zhang et al.   ENERGY

Random Forest based hourly building energy prediction

(2018) Zeyu Wang et al.   ENERGY AND BUILDINGS

Energy and water consumption and carbon footprint of school buildings in hot climate conditions. Results from life cycle assessment

(2018) A.R. Gamarra et al.   JOURNAL OF CLEANER PRODUCTION

Wind Power Forecasting Using Multi-Objective Evolutionary Algorithms for Wavelet Neural Network-Optimized Prediction Intervals

(2018) et al.   Applied Sciences-Basel

An Improved Quantile Regression Neural Network for Probabilistic Load Forecasting

(2018) Wenjie Zhang et al.   IEEE Transactions on Smart Grid

Electricity consumption probability density forecasting method based on LASSO-Quantile Regression Neural Network

(2018) Yaoyao He et al.   APPLIED ENERGY

Time-series clustering based on linear fuzzy information granules

(2018) Lingzi Duan et al.   APPLIED SOFT COMPUTING

Achieving natural ventilation potential in practice: Control schemes and levels of automation

(2018) Yujiao Chen et al.   APPLIED ENERGY

Probabilistic individual load forecasting using pinball loss guided LSTM

(2018) Yi Wang et al.   APPLIED ENERGY

A Data-Driven Fuzzy Information Granulation Approach for Freight Volume Forecasting

(2017) Shen Yin et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Prediction Interval Construction for Byproduct Gas Flow Forecasting Using Optimized Twin Extreme Learning Machine

(2017) Xueying Sun et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

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

An ensemble prediction intervals approach for short-term PV power forecasting

(2017) Qiang Ni et al.   SOLAR ENERGY

Electrical load forecasting models: A critical systematic review

(2017) Corentin Kuster et al.   Sustainable Cities and Society

Defining the Influence Region in neighborhood-scale CFD simulations for natural ventilation design

(2016) Zheming Tong et al.   APPLIED ENERGY

Design of rule-based models through information granulation

(2016) Jeremy Kerr-Wilson et al.   EXPERT SYSTEMS WITH APPLICATIONS

Efficient estimation of flood forecast prediction intervals via single- and multi-objective versions of the LUBE method

(2016) Lei Ye et al.   HYDROLOGICAL PROCESSES

Forecasting Uncertainty in Electricity Smart Meter Data by Boosting Additive Quantile Regression

(2016) Souhaib Ben Taieb et al.   IEEE Transactions on Smart Grid

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

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

Particle swarm optimization for construction of neural network-based prediction intervals

(2013) Hao Quan et al.   NEUROCOMPUTING

Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals

(2013) Hao Quan et al.   IEEE Transactions on Neural Networks and Learning Systems

Comprehensive Review of Neural Network-Based Prediction Intervals and New Advances

(2011) A. Khosravi et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS

Construction of Optimal Prediction Intervals for Load Forecasting Problems

(2010) Abbas Khosravi et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

The design of fuzzy information granules: Tradeoffs between specificity and experimental evidence

(2008) Fusheng Yu et al.   APPLIED SOFT COMPUTING