{"id":"W4408919892","doi":"10.3390/su17073011","title":"Tuning Parameters of Genetic Algorithms for Wind Farm Optimization Using the Design of Experiments Method","year":2025,"lang":"en","type":"article","venue":"Sustainability","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Rimouski","funders":"","keywords":"Genetic algorithm; Algorithm; Mathematical optimization; Optimization algorithm; Computer science; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00610526,0.001591153,0.0008539102,0.0009312277,0.0003991621,0.0007843598,0.0007566967,0.0009494554,0.001259715],"category_scores_gemma":[0.01255166,0.0004633883,0.0009170408,0.0004769555,0.0006564316,0.0004614692,0.0005009374,0.001222255,0.0001542994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006453404,"about_ca_system_score_gemma":0.001221184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001190714,"about_ca_topic_score_gemma":0.001234318,"domain_scores_codex":[0.9974782,0.001623159,0.0001407405,0.0002777892,0.0003610926,0.0001189628],"domain_scores_gemma":[0.9935341,0.0050833,0.0005500527,0.0002768199,0.0005059912,0.00004984837],"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":[0.000631882,0.0007061486,0.00322153,0.0009122068,0.0004085509,0.000114612,0.0001975074,0.8369134,0.02606232,0.009689938,0.0006539826,0.1204879],"study_design_scores_gemma":[0.0003366722,0.001792869,0.002042445,0.00009736031,0.0001937621,0.00005421942,0.00006461031,0.9601201,0.02688603,0.004389267,0.003954753,0.00006791054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06470627,0.0005011416,0.9310111,0.00008809071,0.0001031521,0.0008528088,0.0001076951,0.0005340382,0.002095613],"genre_scores_gemma":[0.4535922,0.000288391,0.5424276,0.00007935352,0.00001627599,0.002894126,0.00009300559,0.00007268097,0.0005362525],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00610526,"threshold_uncertainty_score":0.03228807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03905331586708445,"score_gpt":0.3392882862452004,"score_spread":0.300234970378116,"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."}}