{"id":"W4309684540","doi":"10.1109/iemcon56893.2022.9946597","title":"Harmonics Prediction and Mitigation using Adaptive Neuro Fuzzy Inference System Model based on Hybrid of Wind Solar Driven by DFIG","year":2022,"lang":"en","type":"article","venue":"","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Harmonics; Adaptive neuro fuzzy inference system; Photovoltaic system; Control theory (sociology); Computer science; Wind power; Hybrid system; Renewable energy; Wind speed; Filter (signal processing); Artificial neural network; Fuzzy logic; Fuzzy control system; Engineering; Artificial intelligence; Machine learning; Meteorology; 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":[0.0001855979,0.0003699481,0.0004294055,0.0001805943,0.0002712125,0.0005807052,0.00054702,0.000629392,0.001177562],"category_scores_gemma":[0.0002824251,0.0002046374,0.0004671479,0.0001704183,0.0001577964,0.0004454863,0.0001742964,0.0004313611,0.0001758529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000310075,"about_ca_system_score_gemma":0.000318126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008336031,"about_ca_topic_score_gemma":0.007138938,"domain_scores_codex":[0.9999188,0.00001589069,0.000006023297,0.00002419148,0.00002451804,0.00001044901],"domain_scores_gemma":[0.9999112,0.00003280616,0.00001510327,0.000006467339,0.00003033608,0.000003937762],"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":[0.00006913139,0.00003990234,0.0009112926,0.00005414715,0.00004771238,0.00008643873,0.00004973117,0.9681668,0.004498164,0.00143838,0.0003152418,0.02432316],"study_design_scores_gemma":[0.000003249793,0.0000243267,0.0001882677,0.000003368423,0.000007058709,0.000007502901,0.000004184983,0.9988512,0.000464341,0.0002587143,0.000185043,0.000002683805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1241571,0.0004685151,0.8648297,0.0002215563,0.00009753408,0.00007220211,0.0001625826,0.0007487849,0.009241976],"genre_scores_gemma":[0.9744005,0.0001885337,0.02230648,0.00002513795,0.0000154083,0.00007117242,0.00007712023,0.00001323344,0.002902374],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008336031,"threshold_uncertainty_score":0.01657504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01642893006928331,"score_gpt":0.1959192425507789,"score_spread":0.1794903124814956,"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."}}