{"id":"W4229335382","doi":"10.3390/en15093425","title":"Bayesian Optimization Algorithm-Based Statistical and Machine Learning Approaches for Forecasting Short-Term Electricity Demand","year":2022,"lang":"en","type":"article","venue":"Energies","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Imam Abdulrahman Bin Faisal University; University of Bahrain","keywords":"Nonlinear autoregressive exogenous model; Autoregressive model; Computer science; Bayesian probability; Hyperparameter; Term (time); Algorithm; Statistics; Artificial intelligence; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001633665,0.0009661668,0.001040185,0.001365717,0.0003633745,0.000942185,0.001002106,0.0009120252,0.001181118],"category_scores_gemma":[0.004428401,0.0006985985,0.0007941762,0.001444426,0.0004951872,0.00115541,0.0005822484,0.001128387,0.0003813513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001308553,"about_ca_system_score_gemma":0.002549029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04075239,"about_ca_topic_score_gemma":0.03537901,"domain_scores_codex":[0.9992835,0.0002711408,0.00004963256,0.0001019367,0.0002507848,0.00004297712],"domain_scores_gemma":[0.9986711,0.0008722703,0.000130681,0.00004348725,0.0002575583,0.0000250282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001153043,0.00002837741,0.0008941696,0.00003610276,0.00005356428,0.00001215746,0.00001646714,0.9491035,0.0003197854,0.005860467,0.0004295246,0.04323423],"study_design_scores_gemma":[0.000001872402,0.000004813895,0.0001694689,0.000003819881,0.000002857826,0.000002048898,0.000003196465,0.9974904,0.00006345756,0.001952954,0.000301924,0.000003222478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009036946,0.0006437922,0.9871519,0.0002382856,0.00002561667,0.0000415825,0.00008560262,0.0003019471,0.002474478],"genre_scores_gemma":[0.3815044,0.00217622,0.609288,0.0002443109,0.0001580158,0.000453601,0.0007796991,0.0001706247,0.005225096],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04075239,"threshold_uncertainty_score":0.08103037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02748900254292729,"score_gpt":0.2092400305419548,"score_spread":0.1817510279990275,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}