GEIN: An interpretable benchmarking framework towards all building types based on machine learning

Attention-based interpretable neural network for building cooling load prediction

(2021) Ao Li et al.   APPLIED ENERGY

Examining the feasibility of using open data to benchmark building energy usage in cities: A data science and policy perspective

(2020) Jonathan Roth et al.   ENERGY POLICY

Data-driven estimation of building energy consumption with multi-source heterogeneous data

(2020) Yue Pan et al.   APPLIED ENERGY

Urban building energy modeling: State of the art and future prospects

(2020) F. Johari et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

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

(2020) Pandarasamy Arjunan et al.   APPLIED ENERGY

SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods

(2020) Jonathan Roth et al.   APPLIED ENERGY

A data-driven approach for multi-scale GIS-based building energy modeling for analysis, planning and support decision making

(2020) Usman Ali et al.   APPLIED ENERGY

Application of artificial neutral network and geographic information system to evaluate retrofit potential in public school buildings

(2019) F. Re Cecconi et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Estimating residential energy consumption in metropolitan areas: A microsimulation approach

(2018) Wenwen Zhang et al.   ENERGY

DUE-B: Data-driven urban energy benchmarking of buildings using recursive partitioning and stochastic frontier analysis

(2018) Zheng Yang et al.   ENERGY AND BUILDINGS

Beyond one-hot encoding: Lower dimensional target embedding

(2018) Pau Rodríguez et al.   IMAGE AND VISION COMPUTING

Similarity encoding for learning with dirty categorical variables

(2018) Patricio Cerda et al.   MACHINE LEARNING

A study of city-level building energy efficiency benchmarking system for China

(2018) Zheng Wei et al.   ENERGY AND BUILDINGS

Grading buildings on energy performance using city benchmarking data

(2018) Sokratis Papadopoulos 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

A regression-based approach to estimating retrofit savings using the Building Performance Database

(2016) Travis Walter et al.   APPLIED ENERGY

Applications of machine learning methods to identifying and predicting building retrofit opportunities

(2016) Daniel E. Marasco et al.   ENERGY AND BUILDINGS

Identifying key variables and interactions in statistical models of building energy consumption using regularization

(2015) David Hsu   ENERGY

Cross comparison of empirical and simulated models for calculating residential electricity consumption

(2015) Pamela Torres et al.   ENERGY AND BUILDINGS