Attention-based interpretable neural network for building cooling load prediction

EnergyStar++: Towards more accurate and explanatory building energy benchmarking

(2020) Pandarasamy Arjunan et al.   APPLIED ENERGY

Predicting residential energy consumption using CNN-LSTM neural networks

(2019) Tae-Young Kim et al.   ENERGY

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

(2018) Aowabin Rahman et al.   APPLIED ENERGY

Random Forest based hourly building energy prediction

(2018) Zeyu Wang et al.   ENERGY AND BUILDINGS

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

(2018) Cheng Fan et al.   APPLIED 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

On the development of multi-linear regression analysis to assess energy consumption in the early stages of building design

(2014) Somayeh Asadi et al.   ENERGY AND BUILDINGS

Review of building energy modeling for control and operation

(2014) Xiwang Li et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

An interactive building power demand management strategy for facilitating smart grid optimization

(2013) Xue Xue et al.   APPLIED ENERGY

A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition

(2012) Souhaib Ben Taieb et al.   EXPERT SYSTEMS WITH APPLICATIONS

Permutation importance: a corrected feature importance measure

(2010) André Altmann et al.   BIOINFORMATICS