{"id":"W1673399436","doi":"","title":"PSO and GSA algorithms for fuzzy controller tuning with reduced process small time constant sensitivity","year":2012,"lang":"en","type":"article","venue":"International Conference on System Theory, Control and Computing","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Particle swarm optimization; Sensitivity (control systems); Fuzzy logic; Constant (computer programming); Control theory (sociology); Mathematics; Mathematical optimization; PID controller; Nonlinear system; Algorithm; Computer science; Engineering; Artificial intelligence; Temperature control; Physics; Control (management); Control 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002401951,0.0003489485,0.0006185591,0.0001317073,0.0003291126,0.0004577173,0.0003849785,0.0001071659,0.000001401384],"category_scores_gemma":[0.00009117781,0.0002590252,0.00007719017,0.00009157216,0.0001300695,0.0003150066,0.000100462,0.0001794821,0.00001053456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006966471,"about_ca_system_score_gemma":0.00009108521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002233972,"about_ca_topic_score_gemma":0.000002745287,"domain_scores_codex":[0.9975864,0.0004514894,0.0004666069,0.0005904434,0.0003725216,0.0005325956],"domain_scores_gemma":[0.9975325,0.001062106,0.0003974695,0.0002301185,0.0005492021,0.0002286115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005385232,0.0000574791,0.000648429,0.00006769782,0.0002632278,0.00001413609,0.0008808949,0.00009596629,0.002800075,0.9592741,0.000007974189,0.03535153],"study_design_scores_gemma":[0.008087727,0.0004627124,0.001320841,0.0008465098,0.00007438225,0.0006327208,0.002213882,0.9733889,0.000103636,0.01211635,0.00009034834,0.0006619674],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06275015,0.000392068,0.8847852,0.001020289,0.0007545533,0.00132885,0.00004056004,0.0003167533,0.04861153],"genre_scores_gemma":[0.9972239,0.000002399275,0.00174197,0.000329972,0.0004468602,0.00007550917,0.00000448701,0.00001850259,0.0001564737],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9732929,"threshold_uncertainty_score":0.9999862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02496504082672881,"score_gpt":0.2534541942498401,"score_spread":0.2284891534231113,"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."}}