{"id":"W2560064556","doi":"10.1109/epec.2016.7771715","title":"Anomaly detection in a smart grid using wavelet transform, variance fractal dimension and an artificial neural network","year":2016,"lang":"en","type":"article","venue":"","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Wavelet transform; Wavelet; Artificial neural network; Computer science; Pattern recognition (psychology); Fractal dimension; Fractal; Dimension (graph theory); Artificial intelligence; Variance (accounting); Smart grid; Anomaly detection; Anomaly (physics); Algorithm; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001545627,0.0001159447,0.0001193386,0.00005431319,0.00007978146,0.00002581265,0.00004689108,0.00009212019,0.00001862464],"category_scores_gemma":[0.000006956233,0.0000852866,0.0000222051,0.0001570766,0.00003866202,0.000440952,0.0000102079,0.000108584,0.000003921367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000339174,"about_ca_system_score_gemma":0.000006834498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000112419,"about_ca_topic_score_gemma":0.001714866,"domain_scores_codex":[0.999248,0.00003427341,0.0001760348,0.0001796288,0.00008714887,0.0002748724],"domain_scores_gemma":[0.9997712,0.00003797169,0.00001265885,0.00009689945,0.00001047504,0.00007072791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001552712,0.00007577171,0.00705045,0.00005173681,0.00001914376,0.00005841778,0.0009098228,0.06552389,0.7352619,0.000351622,0.00004924486,0.1904928],"study_design_scores_gemma":[0.0003865499,0.0001129459,0.03939567,0.00005799037,0.000008610833,0.000056844,0.00004574143,0.9051926,0.05367425,0.0004911592,0.0002916785,0.0002860159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9723728,0.00005393383,0.02638837,0.00005396674,0.0007772037,0.0001135493,0.000002231191,0.000112587,0.0001253224],"genre_scores_gemma":[0.9988418,0.00002756947,0.0006315049,0.00002723091,0.0004475346,0.000003593133,9.783387e-7,0.00001408912,0.000005721546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8396686,"threshold_uncertainty_score":0.3477887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01105749262049326,"score_gpt":0.215830070115493,"score_spread":0.2047725774949998,"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."}}