{"id":"W2012102319","doi":"10.3182/20110828-6-it-1002.00938","title":"Gravitational Search Algorithms in Fuzzy Control Systems Tuning","year":2011,"lang":"en","type":"article","venue":"IFAC Proceedings Volumes","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Sensitivity (control systems); Control theory (sociology); Mathematics; Overshoot (microwave communication); Parametric statistics; Fuzzy control system; Fuzzy logic; Mathematical optimization; Algorithm; Computer science; Control (management); Engineering; Artificial intelligence; Statistics","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":[0.002194683,0.0007721739,0.001326236,0.001499672,0.0008604635,0.00130643,0.00116886,0.001900724,0.002612505],"category_scores_gemma":[0.006248095,0.0006162928,0.0004963507,0.001842703,0.001697224,0.001431669,0.001305255,0.001244013,0.0003748537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001063396,"about_ca_system_score_gemma":0.000838624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009964909,"about_ca_topic_score_gemma":0.005694456,"domain_scores_codex":[0.9994441,0.0002779841,0.00002472255,0.00005462594,0.0001630437,0.00003554883],"domain_scores_gemma":[0.9986445,0.000950905,0.000073895,0.00008415606,0.0002120153,0.00003450393],"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":[0.00006260492,0.00002983316,0.0002250588,0.00008688168,0.0000565358,0.00002387388,0.00007169691,0.8419836,0.0007086588,0.06047317,0.002076293,0.09420186],"study_design_scores_gemma":[0.00001227938,0.00001373608,0.0001098635,0.00001003488,0.00000664495,0.000006544963,0.000007542796,0.9787023,0.0001338622,0.02021705,0.000774267,0.000005999572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01207773,0.003066504,0.975979,0.0005166666,0.0001598932,0.00003250417,0.00001738132,0.0002163289,0.007933998],"genre_scores_gemma":[0.6574054,0.002391231,0.3291454,0.0002852408,0.0003674852,0.0001832946,0.00007040724,0.0001917761,0.009959827],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009964909,"threshold_uncertainty_score":0.01981384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02987307217375906,"score_gpt":0.2333005594165393,"score_spread":0.2034274872427802,"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."}}