{"id":"W173431335","doi":"10.1007/978-3-319-13572-4_2","title":"Optimization of Wind Direction Distribution Parameters Using Particle Swarm Optimization","year":2014,"lang":"en","type":"book-chapter","venue":"Advances in intelligent systems and computing","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Particle swarm optimization; Wind power; Computer science; Wind speed; Wind direction; Mathematical optimization; von Mises distribution; Set (abstract data type); Algorithm; von Mises yield criterion; Mathematics; Meteorology; Finite element method; Engineering; Physics; Structural engineering","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":[0.0002072084,0.0002181727,0.0003417909,0.00008152043,0.00006175289,0.0000360837,0.00005873356,0.0001489341,0.000003395519],"category_scores_gemma":[0.00001832684,0.0002352073,0.00004785517,0.00006732398,0.0000382568,0.000126278,0.00002656568,0.0001454541,5.811877e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001161008,"about_ca_system_score_gemma":0.000006231477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003366447,"about_ca_topic_score_gemma":0.000004525613,"domain_scores_codex":[0.9988517,0.00002279577,0.0006034679,0.0002148636,0.0001330843,0.0001740557],"domain_scores_gemma":[0.9994352,0.0001003401,0.0002531511,0.0001153704,0.0000560368,0.00003986945],"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":[0.000004122272,0.000003188279,0.0001294918,0.0002953792,0.00001926944,8.044544e-7,0.00008471551,0.9840401,0.00001053551,0.004501831,0.000001877109,0.01090864],"study_design_scores_gemma":[0.00008048767,0.0000286241,0.000002211938,0.001744648,0.000024361,0.000009777668,0.0000354341,0.9952574,0.0003297407,0.00006089767,0.002207666,0.0002187851],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005623207,0.008003251,0.9779863,8.612939e-7,0.001239849,0.0001745591,0.000009547935,0.00008472569,0.006877645],"genre_scores_gemma":[0.9906269,0.002712291,0.00572267,0.000002617791,0.0001806634,0.000002139026,0.0001086577,0.00005859589,0.0005854403],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9850037,"threshold_uncertainty_score":0.9591475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01580126362208845,"score_gpt":0.2280810372838272,"score_spread":0.2122797736617387,"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."}}