{"id":"W4226505870","doi":"10.3390/designs6020036","title":"Optimized Active Control of a Smart Cantilever Beam Using Genetic Algorithm","year":2022,"lang":"en","type":"article","venue":"Designs","topic":"Aeroelasticity and Vibration Control","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cantilever; Actuator; Active vibration control; Genetic algorithm; Vibration; Control theory (sociology); Vibration control; PID controller; Beam (structure); Position (finance); Computer science; Engineering; Acoustics; Control engineering; Control (management); Structural engineering; Temperature control; Physics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00007309225,0.00009632065,0.0002014729,0.00006600656,0.0001005782,0.000009517183,0.00009246865,0.00002964252,0.0005244219],"category_scores_gemma":[0.00001451537,0.0001094646,0.00006001817,0.0001242605,0.0000207615,0.00006257043,0.00001896682,0.0001255633,0.000004281576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000708016,"about_ca_system_score_gemma":0.00004666751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003832626,"about_ca_topic_score_gemma":0.000001318365,"domain_scores_codex":[0.9993483,0.00005734682,0.0001779064,0.0001006683,0.000152022,0.0001637779],"domain_scores_gemma":[0.9996727,0.0001030612,0.00004141409,0.0001077991,0.00003082332,0.00004418816],"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":[0.0000559859,0.00002367344,0.00002094947,0.00000740644,0.00009055046,0.000007111357,0.0002243187,0.9729685,0.02345494,0.00002031749,0.0001488988,0.002977376],"study_design_scores_gemma":[0.001473127,0.00008324784,0.0002891047,0.000003999732,0.00006048249,0.00000916166,0.00009631504,0.9881,0.009386552,0.00002301905,0.0003572023,0.0001177853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02544819,0.0001039686,0.9736351,0.00001136956,0.0002295332,0.0002385101,0.0001201232,0.00007256681,0.0001406107],"genre_scores_gemma":[0.974075,0.000003301627,0.02569434,0.00006938328,0.00004833108,0.00004865649,0.000004919013,0.00002317565,0.00003289964],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9486268,"threshold_uncertainty_score":0.5742052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02147255582663395,"score_gpt":0.2198065880146695,"score_spread":0.1983340321880355,"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."}}