{"id":"W2382078643","doi":"","title":"THE FUZZY NEURAL NETWORKS MODEL OF SWITCHED RELUCTANCE DRIVERS","year":2000,"lang":"en","type":"article","venue":"","topic":"Induction Heating and Inverter Technology","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Artificial neural network; Switched reluctance motor; Convergence (economics); Estimator; Sigmoid function; Computer science; Nonlinear system; Fuzzy logic; Control theory (sociology); Neuro-fuzzy; Artificial intelligence; Fuzzy control system; Engineering; Mathematics; Control (management)","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":[0.00003686521,0.00005481171,0.00006431211,0.00001481828,0.00005833807,0.000005098049,0.0001074942,0.00006538747,0.00004862446],"category_scores_gemma":[0.000002940961,0.00003966516,0.00002502782,0.00008514995,0.00004700258,0.00004199417,0.000005048393,0.0001332171,0.000008581142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001339798,"about_ca_system_score_gemma":0.000002388478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009104224,"about_ca_topic_score_gemma":0.000006497646,"domain_scores_codex":[0.9996389,0.000004612802,0.0001152898,0.0000595088,0.00004331834,0.0001383439],"domain_scores_gemma":[0.9997812,0.00001341211,0.000008463182,0.0001701995,0.00001271869,0.00001401538],"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":[0.000002477748,0.000002020795,0.00003894967,0.000002103925,0.000007188622,1.407608e-7,0.00006318154,0.9568369,0.0009180703,0.001894457,0.002678442,0.03755601],"study_design_scores_gemma":[0.00006504994,0.000009173263,0.00002369793,0.000002295427,0.00000220028,0.000002249418,0.00004446893,0.9972367,0.001361559,0.0007434948,0.0004625079,0.00004664988],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9150884,0.0001742575,0.01467504,0.0004076823,0.0003032707,0.00007710317,7.79812e-7,0.0007413629,0.06853214],"genre_scores_gemma":[0.9978034,0.0001401825,0.0007179088,0.00004829253,0.00002836995,0.000003957966,4.675855e-7,0.000009141292,0.001248318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.082715,"threshold_uncertainty_score":0.1617498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01003120858449568,"score_gpt":0.1898229271773615,"score_spread":0.1797917185928658,"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."}}