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Evaluating the Impacts of Building Retrofits on U.S. Low-Income Households: A Data-Driven Approach

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inferredcites →https://doi.org/10.1007/978-3-031-01853-4openalex-snapshot
Big Data Integration
inferredcites →https://doi.org/10.1007/s10287-020-00376-3openalex-snapshot
Hyperparameter optimization for recommender systems through Bayesian optimization
inferredcites →https://doi.org/10.1007/s10489-020-01766-5openalex-snapshot
A hybrid two-stage financial stock forecasting algorithm based on clustering and ensemble learning
inferredcites →https://doi.org/10.1007/s12205-022-1984-2openalex-snapshot
Determinants of Electricity Consumption of Energy-Vulnerable Group Using Ensemble Gradient-Boosting Algorithm
inferredcites →https://doi.org/10.1016/j.buildenv.2005.11.001openalex-snapshot
European residential buildings and empirical assessment of the Hellenic building stock, energy consumption, emissions and potential energy savings
inferredcites →https://doi.org/10.1016/j.buildenv.2017.01.020openalex-snapshot
An optimization framework for building energy retrofits decision-making
inferredcites →https://doi.org/10.1016/j.buildenv.2017.12.027openalex-snapshot
Selection of optimization objectives for decision-making in building energy retrofits
inferredcites →https://doi.org/10.1016/j.buildenv.2021.107847openalex-snapshot
Health and financial benefits of weatherizing low-income homes in the southeastern United States
inferredcites →https://doi.org/10.1016/j.buildenv.2025.112847openalex-snapshot
A Framework for Facilitating Low-Income Net-Zero Energy Housing Delivery in Developing Countries: Insights from a Practical Case in South Africa
inferredcites →https://doi.org/10.1016/j.dibe.2020.100037openalex-snapshot
Energy consumption prediction by using machine learning for smart building: Case study in Malaysia
inferredcites →https://doi.org/10.1016/j.egyr.2021.02.006openalex-snapshot
Prediction of home energy consumption based on gradient boosting regression tree
inferredcites →https://doi.org/10.1016/j.enbuild.2010.04.006openalex-snapshot
A decision tree method for building energy demand modeling
inferredcites →https://doi.org/10.1016/j.enbuild.2012.08.018openalex-snapshot
Existing building retrofits: Methodology and state-of-the-art
inferredcites →https://doi.org/10.1016/j.enbuild.2016.12.028openalex-snapshot
Energy retrofit and conservation of a historic building using multi-objective optimization and an analytic hierarchy process
inferredcites →https://doi.org/10.1016/j.enbuild.2017.04.038openalex-snapshot
Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption
inferredcites →https://doi.org/10.1016/j.enbuild.2018.04.008openalex-snapshot
Random Forest based hourly building energy prediction
inferredcites →https://doi.org/10.1016/j.enbuild.2023.112965openalex-snapshot
Investigating the application of a commercial and residential energy consumption prediction model for urban Planning scenarios with Machine Learning and Shapley Additive explanation methods
inferredcites →https://doi.org/10.1016/j.enconman.2008.01.035openalex-snapshot
Annual electricity consumption forecasting by neural network in high energy consuming industrial sectors
inferredcites →https://doi.org/10.1016/j.enconman.2016.12.094openalex-snapshot
A novel implementation of kNN classifier based on multi-tupled meteorological input data for wind power prediction
inferredcites →https://doi.org/10.1016/j.energy.2018.04.161openalex-snapshot
Estimating residential energy consumption in metropolitan areas: A microsimulation approach
inferredcites →https://doi.org/10.1016/j.enpol.2012.05.053openalex-snapshot
Policy options for the split incentive: Increasing energy efficiency for low-income renters
inferredcites →https://doi.org/10.1016/j.enpol.2016.07.048openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.enpol.2017.04.002openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.erss.2025.104188openalex-snapshot
The unsung heroes of Norway's sustainability transitions? Making visible the “invisible” energy citizenship of low-income households
inferredcites →https://doi.org/10.1016/j.erss.2025.104207openalex-snapshot
Energy burden: Exploring the intersection of race, income, and community characteristics across the United States
inferredcites →https://doi.org/10.1016/j.inffus.2013.05.003openalex-snapshot
An approach to implement data fusion techniques in wireless sensor networks using genetic machine learning algorithms
inferredcites →https://doi.org/10.1016/j.inffus.2019.12.001openalex-snapshot
A survey on machine learning for data fusion
inferredcites →https://doi.org/10.1016/j.jobe.2024.109305openalex-snapshot
Analyzing energy performance in American low income households: A DataDriven approach with machine learning insights
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Uncovering energy use patterns of public primary and secondary schools through district-wide benchmarking
inferredcites →https://doi.org/10.1016/j.rser.2017.01.145openalex-snapshot
Energy retrofits in historic and traditional buildings: A review of problems and methods
inferredcites →https://doi.org/10.1016/j.rser.2017.04.095openalex-snapshot
A review of data-driven building energy consumption prediction studies
inferredcites →https://doi.org/10.1016/j.rser.2020.110114openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.scs.2020.102128openalex-snapshot
Prediction of energy consumption in hotel buildings via support vector machines
inferredcites →https://doi.org/10.1016/j.scs.2022.104141openalex-snapshot
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inferredcites →https://doi.org/10.1038/s41893-024-01314-wopenalex-snapshot
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inferredcites →https://doi.org/10.1061/9780784485279.032openalex-snapshot
Creating a Large-Scale National Residential Building Energy Dataset Using a Two-Stage Machine Learning Approach
inferredcites →https://doi.org/10.1080/01944363.2019.1647446openalex-snapshot
Energy Cost Burdens for Low-Income and Minority Households
inferredcites →https://doi.org/10.1080/0952813x.2015.1056242openalex-snapshot
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inferredcites →https://doi.org/10.1080/13549839.2015.1136995openalex-snapshot
A community-based approach to low-income residential energy efficiency participation barriers
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inferredcites →https://doi.org/10.1109/ipdpsw.2015.12openalex-snapshot
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inferredcites →https://doi.org/10.1109/irs.2012.6233354openalex-snapshot
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inferredcites →https://doi.org/10.14257/ijast.2017.101.02openalex-snapshot
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inferredcites →https://doi.org/10.14257/ijsh.2016.10.2.10openalex-snapshot
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inferredcites →https://doi.org/10.2166/wcc.2023.331openalex-snapshot
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Filtering and Housing Standards: A Conceptual Analysis
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Recent Innovations in Reducing Home Energy Costs and Improving Resilience for Low- and Moderate-Income Renters and Homeowners
inferredcites →https://doi.org/10.24148/cdrb2023-4openalex-snapshot
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