{"id":"W1557973604","doi":"10.1109/isie.2003.1267960","title":"A novel genetic algorithm based fuzzy logic controller for IPM synchronous motor drive","year":2004,"lang":"en","type":"article","venue":"","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Control theory (sociology); Fuzzy logic; Genetic algorithm; Controller (irrigation); Computer science; Digital signal processor; Electronic speed control; Scheme (mathematics); Control engineering; Motor drive; Fuzzy control system; Synchronous motor; Vector control; Digital signal processing; Engineering; Induction motor; Control (management); Mathematics; Artificial intelligence; Computer hardware; Electrical engineering","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":[0.0001944945,0.000370472,0.0002911057,0.0002759139,0.0002479588,0.0004449878,0.0007387355,0.0005750774,0.001002767],"category_scores_gemma":[0.0003967807,0.00009647363,0.0001943011,0.0002371534,0.0002569471,0.0002896324,0.0001581194,0.0004750682,0.0002705914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003847125,"about_ca_system_score_gemma":0.0004103837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002671022,"about_ca_topic_score_gemma":0.002578155,"domain_scores_codex":[0.9998296,0.00001965284,0.000008720022,0.00003895708,0.00008958961,0.00001335116],"domain_scores_gemma":[0.9999222,0.00001561141,0.00001157487,0.000005449123,0.00003946357,0.00000580397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001950008,0.0001593363,0.0008009215,0.0003454366,0.00008588782,0.000456027,0.0001436056,0.2370925,0.1196067,0.01555873,0.003787668,0.6217682],"study_design_scores_gemma":[0.00008991612,0.000293298,0.0006636045,0.0000244085,0.00004023119,0.000272878,0.00001438337,0.9665526,0.01786637,0.002464805,0.01168963,0.00002789983],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01850853,0.0004384439,0.9758045,0.0001101855,0.0001451635,0.00007292264,0.0000312641,0.0007929659,0.004096021],"genre_scores_gemma":[0.6362992,0.0005060486,0.356526,0.0002344544,0.00007857124,0.0002126335,0.0001196264,0.00004155331,0.005981907],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002671022,"threshold_uncertainty_score":0.005310893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01248814971279247,"score_gpt":0.2183285344838394,"score_spread":0.2058403847710469,"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."}}