{"id":"W2621129873","doi":"10.1109/ever.2017.7935920","title":"Power factor improvement using adaptive fuzzy logic control based D-STATCOM","year":2017,"lang":"en","type":"article","venue":"","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Control theory (sociology); Harmonics; Power factor; Robustness (evolution); AC power; Overshoot (microwave communication); Feed forward; Fuzzy logic; Computer science; Fuzzy control system; Electric power system; Power (physics); Engineering; Control engineering; Control (management); Voltage; Physics; Telecommunications; Electrical engineering; Artificial intelligence","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":[0.00016291,0.0004168057,0.0002035114,0.0003120257,0.0002091376,0.0004744449,0.0003763974,0.0002974402,0.001580338],"category_scores_gemma":[0.0002973679,0.00009245569,0.0002330085,0.0003574421,0.0001459936,0.0002614801,0.0001934561,0.0002908131,0.0002258053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002645053,"about_ca_system_score_gemma":0.0002266934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00215526,"about_ca_topic_score_gemma":0.003806966,"domain_scores_codex":[0.9998887,0.00001777801,0.0000122239,0.00002852926,0.00004207867,0.00001065633],"domain_scores_gemma":[0.9998773,0.00003215861,0.00002831041,0.00001049808,0.00004682965,0.000004799373],"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":[0.0007293342,0.0003847135,0.002455056,0.0004608062,0.0001122039,0.000344968,0.0001234736,0.4361865,0.120851,0.004511915,0.002350363,0.4314896],"study_design_scores_gemma":[0.00009272427,0.0005791881,0.00160443,0.00002535289,0.00006440285,0.0001077254,0.00002840087,0.9734787,0.01991669,0.001684202,0.002403742,0.00001441745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1716896,0.0007525552,0.8070526,0.0002663508,0.0001324913,0.0001190151,0.0001293111,0.001790836,0.01806725],"genre_scores_gemma":[0.9814636,0.0001365009,0.01694738,0.00004833519,0.00001516936,0.00001902879,0.00004618911,0.00001156228,0.001312197],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00215526,"threshold_uncertainty_score":0.005286694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01652758219416315,"score_gpt":0.2239140339952368,"score_spread":0.2073864518010736,"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."}}