{"id":"W2037958515","doi":"10.1007/s00466-003-0525-1","title":"Optimal shape control of functionally graded smart plates using genetic algorithms","year":2004,"lang":"en","type":"article","venue":"Computational Mechanics","topic":"Aeroelasticity and Vibration Control","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Genetic algorithm; Voltage; Displacement (psychology); Optimal control; Volume fraction; Actuator; Smart material; Control theory (sociology); Piezoelectricity; Materials science; Algorithm; Mathematics; Computer science; Engineering; Mathematical optimization; Control (management); Composite material","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":[0.000455396,0.0006637729,0.0007116008,0.0006140434,0.0003532222,0.0006690915,0.0009163208,0.000830121,0.001235274],"category_scores_gemma":[0.001069012,0.0004439912,0.0004549506,0.0003286222,0.001028835,0.0003628077,0.000638365,0.000432884,0.000169618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000693241,"about_ca_system_score_gemma":0.0006834721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004838067,"about_ca_topic_score_gemma":0.005317714,"domain_scores_codex":[0.9998757,0.00003307021,0.000004935485,0.00002120194,0.00003869478,0.00002638214],"domain_scores_gemma":[0.9996347,0.0001580098,0.00006418824,0.00002704111,0.00008932783,0.00002657299],"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":[0.00002285963,0.00001417213,0.00009579822,0.000009064005,0.000006440805,0.00001835409,0.00001665284,0.9885731,0.00189106,0.002127714,0.00008484266,0.007139858],"study_design_scores_gemma":[0.00001050239,0.0000192473,0.00003428768,0.000001907362,0.00000282365,0.000002757152,0.000005254235,0.9984097,0.0003491066,0.001093931,0.00006808509,0.00000252328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2250144,0.0002109496,0.764455,0.0001949243,0.00008988121,0.00007842007,0.00003120147,0.0003308633,0.009594417],"genre_scores_gemma":[0.9485357,0.00006905806,0.04917748,0.0000435434,0.00001259612,0.00006757184,0.00002308809,0.00003681558,0.002034183],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004838067,"threshold_uncertainty_score":0.009619832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01645522156942511,"score_gpt":0.2137801586723363,"score_spread":0.1973249371029112,"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."}}