{"id":"W4414098802","doi":"10.23977/jeeem.2025.080114","title":"Parameter Tuning Method of Reluctance Motor Based on Hybrid Optimization Strategy","year":2025,"lang":"en","type":"article","venue":"Journal of Electrotechnology Electrical Engineering and Management","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Particle swarm optimization; Multi-swarm optimization; Convergence (economics); Meta-optimization; Controller (irrigation); Genetic algorithm; Noise (video); Optimization problem","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004506499,0.0006712852,0.000667694,0.0005688147,0.00027617,0.0006899603,0.0006978492,0.0005113556,0.001158347],"category_scores_gemma":[0.0005431403,0.0003246413,0.0004486856,0.0003645211,0.0003320026,0.0005960946,0.0003432401,0.000313912,0.0002862749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002592156,"about_ca_system_score_gemma":0.0002907981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001828738,"about_ca_topic_score_gemma":0.001343073,"domain_scores_codex":[0.9996957,0.00006785949,0.0000246921,0.00007765392,0.0001126453,0.00002160344],"domain_scores_gemma":[0.9998277,0.00004881561,0.00003485023,0.00001696668,0.00006454953,0.000006982687],"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":[0.0002377788,0.0001020847,0.001428938,0.000471261,0.0001708531,0.0001819749,0.0002824302,0.5901205,0.06736736,0.01374676,0.001888285,0.3240018],"study_design_scores_gemma":[0.00003175894,0.0000900693,0.0003294517,0.000009695505,0.00001951667,0.0000723487,0.000016039,0.9932459,0.003639943,0.0008780133,0.00165225,0.00001509736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0186691,0.00036179,0.9771487,0.00005876944,0.00003041174,0.00003905145,0.000007810559,0.0003548936,0.003329641],"genre_scores_gemma":[0.8428107,0.0004317665,0.1518906,0.00006782068,0.00003532167,0.0001489284,0.00005264936,0.0001099574,0.004452168],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001828738,"threshold_uncertainty_score":0.003875077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004200636414675158,"score_gpt":0.2087311448172278,"score_spread":0.2045305084025527,"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."}}