{"id":"W1540309639","doi":"10.1109/ccece.2015.7129352","title":"Open circuit fault diagnosis for the power electronic converter stages using ANFIS algorithm","year":2015,"lang":"en","type":"article","venue":"","topic":"Silicon Carbide Semiconductor Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Adaptive neuro fuzzy inference system; Fault (geology); Rectifier (neural networks); Power (physics); Inverter; Boost converter; Computer science; Electronic engineering; Voltage; Control theory (sociology); Algorithm; Fuzzy logic; Engineering; Fuzzy control system; Electrical engineering; Artificial intelligence; Artificial neural network","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":[0.0003967174,0.0008022923,0.0005345072,0.0005228449,0.0003548487,0.0004460153,0.0004822442,0.0009448053,0.00143141],"category_scores_gemma":[0.00108177,0.0002476453,0.0004366885,0.0002333614,0.0002395475,0.0004153722,0.0002323365,0.0006189927,0.0001678447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005115041,"about_ca_system_score_gemma":0.0005445012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009795339,"about_ca_topic_score_gemma":0.006786042,"domain_scores_codex":[0.9998522,0.00003156952,0.00001556127,0.00003478311,0.0000474203,0.00001835217],"domain_scores_gemma":[0.9997182,0.0001603623,0.00003434398,0.00000789367,0.0000720783,0.000006997861],"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":[0.0001118782,0.00004934793,0.000977125,0.0001173917,0.00004262907,0.0001231087,0.00008455323,0.8863505,0.005167079,0.002192759,0.0006576788,0.1041259],"study_design_scores_gemma":[0.000005018937,0.00001927937,0.000136076,0.00000673896,0.000004447279,0.000009744646,0.000005661826,0.9987317,0.0006123853,0.0003246366,0.0001425086,0.000001775216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05013234,0.0004442685,0.9447602,0.0001934149,0.00007068615,0.0001146907,0.00006719469,0.0009019903,0.003315161],"genre_scores_gemma":[0.8674646,0.0002402939,0.1295609,0.00005273736,0.00002781492,0.0002224106,0.0001082908,0.00001931385,0.002303654],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009795339,"threshold_uncertainty_score":0.01947665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06369189330192912,"score_gpt":0.287369819450356,"score_spread":0.2236779261484269,"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."}}