{"id":"W4313361472","doi":"10.3390/buildings13010080","title":"An Effective Metaheuristic Approach for Building Energy Optimization Problems","year":2022,"lang":"en","type":"article","venue":"Buildings","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Metaheuristic; Mathematical optimization; Computer science; Global optimization; Optimization problem; Test functions for optimization; Algorithm; Multi-swarm optimization; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002978825,0.0001784745,0.0001872297,0.0001455722,0.0003190302,0.00005662044,0.0002183457,0.00004476173,0.00003308947],"category_scores_gemma":[0.00002524703,0.0001991781,0.00007717234,0.000297723,0.00001503858,0.0001792236,0.00004990037,0.0001334486,1.963687e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001165714,"about_ca_system_score_gemma":0.000007782386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003313632,"about_ca_topic_score_gemma":8.303066e-7,"domain_scores_codex":[0.9990141,0.00004284153,0.0001921563,0.0002789337,0.0001584878,0.0003134305],"domain_scores_gemma":[0.999592,0.00008421291,0.00004927177,0.0001664444,0.00003216662,0.0000758988],"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":[0.000009803806,0.00003208217,0.00002742593,0.00006400287,0.00004088543,7.994058e-7,0.0002068969,0.9758947,0.007777283,0.00798328,0.0002753355,0.007687539],"study_design_scores_gemma":[0.0003194734,0.0001362924,0.000007187663,0.000009359148,0.00003587317,0.0000160687,0.00004556288,0.9755901,0.004312864,0.000378114,0.01889248,0.0002566398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01814837,0.0004030484,0.9781722,0.000005883185,0.000353686,0.0002783899,0.00002394315,0.0005017336,0.002112688],"genre_scores_gemma":[0.8478726,0.000009418129,0.1507397,0.00004072526,0.0001593572,0.0009121053,0.0001213022,0.00008123414,0.00006356553],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8297243,"threshold_uncertainty_score":0.8122249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007925408829379282,"score_gpt":0.20504578427065,"score_spread":0.1971203754412707,"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."}}