{"id":"W2025542264","doi":"10.1016/j.ins.2010.12.014","title":"Type-2 fuzzy neural networks with fuzzy clustering and differential evolution optimization","year":2011,"lang":"en","type":"article","venue":"Information Sciences","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":161,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Neuro-fuzzy; Defuzzification; Fuzzy set operations; Fuzzy classification; Fuzzy logic; Fuzzy number; Fuzzy rule; Computer science; Cluster analysis; Artificial intelligence; Fuzzy associative matrix; Fuzzy clustering; Data mining; Adaptive neuro fuzzy inference system; Machine learning; Fuzzy control system; Fuzzy set","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":[0.001486862,0.0007843493,0.001171783,0.0007144912,0.0007142427,0.001130133,0.001873336,0.002389749,0.001906627],"category_scores_gemma":[0.003703862,0.0005734786,0.0009293726,0.001272049,0.0005953767,0.00152276,0.001207552,0.001004029,0.0004406187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001098109,"about_ca_system_score_gemma":0.0008254553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005460038,"about_ca_topic_score_gemma":0.004891299,"domain_scores_codex":[0.9995068,0.000180346,0.00003591237,0.00009747603,0.0001460978,0.00003339197],"domain_scores_gemma":[0.9994967,0.0002312432,0.00004841636,0.00004360484,0.000162144,0.00001792737],"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":[0.00006158809,0.00003257937,0.0002610547,0.00007872393,0.00005379376,0.00003992222,0.00004526097,0.9268352,0.001011078,0.02008139,0.0008512082,0.05064822],"study_design_scores_gemma":[0.000003365287,0.00000685855,0.00003083613,0.000003528254,0.000003761542,0.000006943891,0.000002080064,0.9969331,0.000188072,0.002640775,0.0001770965,0.000003526865],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0128219,0.0005037414,0.9829056,0.0001428219,0.0001126202,0.00005909292,0.00003129934,0.00008818097,0.003334702],"genre_scores_gemma":[0.4814625,0.0005526504,0.5067477,0.0001580036,0.0001598704,0.0004333812,0.0001354797,0.00007293346,0.01027751],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005460038,"threshold_uncertainty_score":0.01085651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02060442331164855,"score_gpt":0.205568381667854,"score_spread":0.1849639583562054,"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."}}