Research graph
References from Day-Ahead XGBoost Forecasting of Aggregated Residential Load: Accuracy and SHAP Ranking Agreement Across Experimental Configurations. Local targets link to admitted publications; unresolved targets remain external evidence.
Energy Models for Demand Forecasting—A Review
10.1016/j.rser.2011.08.014 · 2012 · External reference
10.3390/en16104060
10.3390/en16104060 · External reference
Review of Low Voltage Load Forecasting: Methods, Applications, and Recommendations
10.1016/j.apenergy.2021.117798 · 2021 · External reference
10.3390/en14196200
10.3390/en14196200 · External reference
10.3390/en16186726
10.3390/en16186726 · External reference
Determinants and Approaches of Household Energy Consumption: A Review
10.1016/j.egyr.2023.08.026 · 2023 · External reference
Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network
10.1109/tsg.2017.2753802 · 2019 · External reference
Short-Term Load Forecasts for Municipal and Household Consumers—A Case Study in Selected Areas of Poland
10.1109/access.2026.3675870 · 2026 · External reference
Thermal Comfort and Building Energy Consumption Implications—A Review
10.1016/j.apenergy.2013.10.062 · 2014 · External reference
What is the Effect of Weather on Household Electricity Consumption? Empirical Evidence from Ireland
10.1016/j.eneco.2022.106023 · 2022 · External reference
A Comprehensive Review of the Load Forecasting Techniques Using Single and Hybrid Predictive Models
10.1109/access.2020.3010702 · 2020 · External reference
10.3390/en14102737
10.3390/en14102737 · External reference
10.3390/en14237952
10.3390/en14237952 · External reference
10.3390/en10101547
10.3390/en10101547 · External reference
Season Specific Approach for Short-Term Load Forecasting Based on Hybrid FA-SVM and Similarity Concept
10.1016/j.energy.2019.03.010 · 2019 · External reference
10.1145/2939672.2939785
10.1145/2939672.2939785 · External reference
10.3390/en15207547
10.3390/en15207547 · External reference
10.3390/info12020050
10.3390/info12020050 · External reference
10.3390/en18195144
10.3390/en18195144 · External reference
Explainability and Interpretability in Electric Load Forecasting Using Machine Learning Techniques—A Review
10.1016/j.egyai.2024.100358 · 2024 · External reference
Explainable Artificial Intelligence (XAI) Techniques for Energy and Power Systems: Review, Challenges and Opportunities
10.1016/j.egyai.2022.100169 · 2022 · External reference
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI
10.1016/j.inffus.2019.12.012 · 2020 · External reference
Unresolved reference
External reference
From Local Explanations to Global Understanding with Explainable AI for Trees
10.1038/s42256-019-0138-9 · 2020 · External reference
Electricity Consumption Forecasting: An Approach Using Cooperative Ensemble Learning with SHapley Additive exPlanations
10.3390/forecast6030042 · 2024 · External reference
All Models are Wrong, but Many are Useful: Learning a Variable’s Importance by Studying an Entire Class of Prediction Models Simultaneously
2019 · External reference
Unresolved reference
External reference
General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models
10.1007/978-3-031-04083-2_4 · 2022 · External reference
SHAP Value-Based Feature Importance Analysis for Short-Term Load Forecasting
10.1007/s42835-022-01161-9 · 2023 · External reference
10.1109/isgt50606.2022.9817538
10.1109/isgt50606.2022.9817538 · External reference
Power Load Forecasting and Interpretable Models Based on GS_XGBoost and SHAP
10.1088/1742-6596/2195/1/012028 · 2022 · External reference
Interpretable Short-Term Electrical Load Forecasting Scheme Using Cubist
10.1155/2022/6892995 · 2022 · External reference
10.1145/3580305.3599848
10.1145/3580305.3599848 · External reference
Harnessing eXplainable Artificial Intelligence for Feature Selection in Time Series Energy Forecasting: A Comparative Analysis of Grad-CAM and SHAP
10.1016/j.apenergy.2023.122079 · 2024 · External reference
Selection of Estimation Window in the Presence of Breaks
10.1016/j.jeconom.2006.03.010 · 2007 · External reference
Improving Forecast Accuracy by Combining Recursive and Rolling Forecasts
10.1111/j.1468-2354.2009.00533.x · 2009 · External reference
Comparing Predictive Accuracy
10.1080/07350015.1995.10524599 · 1995 · External reference
Testing the Equality of Prediction Mean Squared Errors
10.1016/s0169-2070(96)00719-4 · 1997 · External reference
10.3390/en16031434
10.3390/en16031434 · External reference
10.1137/1.9781611972771.42
10.1137/1.9781611972771.42 · External reference
Hyperparameter Self-Tuning for Data Streams
10.1016/j.inffus.2021.04.011 · 2021 · External reference
General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models
10.1007/978-3-031-04083-2_4 · ExternalCitation · doi-reference
SHAP Value-Based Feature Importance Analysis for Short-Term Load Forecasting
10.1007/s42835-022-01161-9 · ExternalCitation · doi-reference
Thermal Comfort and Building Energy Consumption Implications—A Review
10.1016/j.apenergy.2013.10.062 · ExternalCitation · doi-reference
Review of Low Voltage Load Forecasting: Methods, Applications, and Recommendations
10.1016/j.apenergy.2021.117798 · ExternalCitation · doi-reference
Harnessing eXplainable Artificial Intelligence for Feature Selection in Time Series Energy Forecasting: A Comparative Analysis of Grad-CAM and SHAP
10.1016/j.apenergy.2023.122079 · ExternalCitation · doi-reference
Explainable Artificial Intelligence (XAI) Techniques for Energy and Power Systems: Review, Challenges and Opportunities
10.1016/j.egyai.2022.100169 · ExternalCitation · doi-reference
Explainability and Interpretability in Electric Load Forecasting Using Machine Learning Techniques—A Review
10.1016/j.egyai.2024.100358 · ExternalCitation · doi-reference
Determinants and Approaches of Household Energy Consumption: A Review
10.1016/j.egyr.2023.08.026 · ExternalCitation · doi-reference
What is the Effect of Weather on Household Electricity Consumption? Empirical Evidence from Ireland
10.1016/j.eneco.2022.106023 · ExternalCitation · doi-reference
Season Specific Approach for Short-Term Load Forecasting Based on Hybrid FA-SVM and Similarity Concept
10.1016/j.energy.2019.03.010 · ExternalCitation · doi-reference
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI
10.1016/j.inffus.2019.12.012 · ExternalCitation · doi-reference
Hyperparameter Self-Tuning for Data Streams
10.1016/j.inffus.2021.04.011 · ExternalCitation · doi-reference
Selection of Estimation Window in the Presence of Breaks
10.1016/j.jeconom.2006.03.010 · ExternalCitation · doi-reference
Energy Models for Demand Forecasting—A Review
10.1016/j.rser.2011.08.014 · ExternalCitation · doi-reference
Testing the Equality of Prediction Mean Squared Errors
10.1016/s0169-2070(96)00719-4 · ExternalCitation · doi-reference
From Local Explanations to Global Understanding with Explainable AI for Trees
10.1038/s42256-019-0138-9 · ExternalCitation · doi-reference
Comparing Predictive Accuracy
10.1080/07350015.1995.10524599 · ExternalCitation · doi-reference
Power Load Forecasting and Interpretable Models Based on GS_XGBoost and SHAP
10.1088/1742-6596/2195/1/012028 · ExternalCitation · doi-reference
A Comprehensive Review of the Load Forecasting Techniques Using Single and Hybrid Predictive Models
10.1109/access.2020.3010702 · ExternalCitation · doi-reference
Short-Term Load Forecasts for Municipal and Household Consumers—A Case Study in Selected Areas of Poland
10.1109/access.2026.3675870 · ExternalCitation · doi-reference
10.1109/isgt50606.2022.9817538
10.1109/isgt50606.2022.9817538 · ExternalCitation · doi-reference
Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network
10.1109/tsg.2017.2753802 · ExternalCitation · doi-reference
Improving Forecast Accuracy by Combining Recursive and Rolling Forecasts
10.1111/j.1468-2354.2009.00533.x · ExternalCitation · doi-reference
10.1137/1.9781611972771.42
10.1137/1.9781611972771.42 · ExternalCitation · doi-reference
10.1145/2939672.2939785
10.1145/2939672.2939785 · ExternalCitation · doi-reference
10.1145/3580305.3599848
10.1145/3580305.3599848 · ExternalCitation · doi-reference
Interpretable Short-Term Electrical Load Forecasting Scheme Using Cubist
10.1155/2022/6892995 · ExternalCitation · doi-reference
10.3390/en10101547
10.3390/en10101547 · ExternalCitation · doi-reference
10.3390/en14102737
10.3390/en14102737 · ExternalCitation · doi-reference
10.3390/en14196200
10.3390/en14196200 · ExternalCitation · doi-reference
10.3390/en14237952
10.3390/en14237952 · ExternalCitation · doi-reference
10.3390/en15207547
10.3390/en15207547 · ExternalCitation · doi-reference
10.3390/en16031434
10.3390/en16031434 · ExternalCitation · doi-reference
10.3390/en16104060
10.3390/en16104060 · ExternalCitation · doi-reference
10.3390/en16186726
10.3390/en16186726 · ExternalCitation · doi-reference
10.3390/en18195144
10.3390/en18195144 · ExternalCitation · doi-reference
Electricity Consumption Forecasting: An Approach Using Cooperative Ensemble Learning with SHapley Additive exPlanations
10.3390/forecast6030042 · ExternalCitation · doi-reference
10.3390/info12020050
10.3390/info12020050 · ExternalCitation · doi-reference
