{"id":"W3217663633","doi":"10.1109/epec52095.2021.9621395","title":"The Augmented Unscented H-infinity Transform with H-infinity Filtering for Effective Wind Speed Estimation in Wind Turbines","year":2021,"lang":"en","type":"article","venue":"","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Wind speed; Wind power; Control theory (sociology); Turbine; Robustness (evolution); Anemometer; Computer science; Unscented transform; Kalman filter; Engineering; Extended Kalman filter; Meteorology; Control (management); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002176792,0.0002052884,0.0002018359,0.00005762947,0.0001577272,0.00007832007,0.00008940726,0.00007246392,0.00002869601],"category_scores_gemma":[0.00008611042,0.0001470271,0.00006260986,0.0003309404,0.00003308492,0.0001853617,0.00001405576,0.0001845822,0.000003286478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008595181,"about_ca_system_score_gemma":0.00002939702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000574249,"about_ca_topic_score_gemma":0.0009131198,"domain_scores_codex":[0.9990627,0.00003038357,0.0002566386,0.0001842332,0.000130709,0.0003352893],"domain_scores_gemma":[0.9992689,0.0004050692,0.00002967535,0.0001672111,0.00007148502,0.00005769005],"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":[0.0003347814,0.00009270893,0.003161198,0.0004213417,0.0002615703,0.00003091264,0.001531495,0.9364136,0.01286321,0.001434441,0.0002226706,0.04323207],"study_design_scores_gemma":[0.003286506,0.0001876654,0.01392633,0.0004858598,0.00005248747,0.00003306487,0.0004284348,0.8379712,0.136036,0.0004419082,0.006642683,0.0005078175],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9430147,0.0001420591,0.03001871,0.0001815991,0.0005046059,0.0006531202,0.00002462801,0.0002860375,0.02517448],"genre_scores_gemma":[0.9975,0.00002315607,0.001861746,0.00002726653,0.00005150104,0.00001351643,0.00007064193,0.00003564273,0.0004165173],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1231728,"threshold_uncertainty_score":0.5995591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009105825444986658,"score_gpt":0.2200653413001633,"score_spread":0.2109595158551766,"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."}}