{"id":"W2325628659","doi":"10.2495/acar140391","title":"Identification of Colman–Hodgdon hysteresis model of a piezoelectric actuator using particle swarm optimization technique and genetic algorithm","year":2015,"lang":"en","type":"article","venue":"WIT transactions on engineering sciences","topic":"Piezoelectric Actuators and Control","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Particle swarm optimization; Hysteresis; Actuator; Genetic algorithm; Identification (biology); Piezoelectricity; Computer science; Control theory (sociology); Algorithm; Materials science; Physics; Artificial intelligence; Composite material; Condensed matter physics; Control (management); Machine learning","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":[],"consensus_categories":[],"category_scores_codex":[0.0002264299,0.0001150525,0.0001624586,0.0002367259,0.00005002112,0.00002230935,0.0001127385,0.00005600914,0.000002118934],"category_scores_gemma":[0.00001654265,0.0001154149,0.00003308949,0.0006889889,0.00005011947,0.0001878332,0.000001672909,0.00007206576,3.199889e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005813083,"about_ca_system_score_gemma":0.00005215037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001218281,"about_ca_topic_score_gemma":6.045298e-7,"domain_scores_codex":[0.9991388,0.00001176593,0.0003119977,0.0001505968,0.0002168304,0.0001700154],"domain_scores_gemma":[0.9996543,0.00003470297,0.00006118825,0.0001157107,0.00006349872,0.00007060025],"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":[0.00000320159,0.00002241081,0.000007698955,0.00002519818,0.00001434251,1.771359e-7,0.00009548356,0.9343401,0.04123345,0.0000203701,9.066954e-7,0.02423669],"study_design_scores_gemma":[0.0001613706,0.00008492392,0.00001818122,0.00002240615,0.00003410549,0.000005807092,0.00003045438,0.9088479,0.09065877,0.00003320729,8.026454e-7,0.0001021022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1964095,0.0001502893,0.8031245,0.000005496942,0.00004751288,0.0001696782,0.000009289317,0.00007610539,0.000007574751],"genre_scores_gemma":[0.9095856,0.00004730998,0.09030495,0.000001912374,0.000007776122,0.00003281415,2.972076e-7,0.00001412746,0.000005207927],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7131761,"threshold_uncertainty_score":0.4706484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01582872641696622,"score_gpt":0.2129710187917014,"score_spread":0.1971422923747351,"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."}}