{"id":"W2131854103","doi":"","title":"Electricity Price Forecasting in Ontario Electricity Market Using Wavelet Transform in Artificial Neural Network Based Model","year":2008,"lang":"en","type":"article","venue":"","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Autoregressive integrated moving average; Artificial neural network; Electricity market; Heuristic; Wavelet; Computer science; Econometrics; Wavelet transform; Time series; Electricity; Artificial intelligence; Machine learning; Mathematics; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002814284,0.0002209918,0.0001935021,0.0002210614,0.0002094577,0.0003820023,0.0003806812,0.0002948014,0.0008864588],"category_scores_gemma":[0.0009945097,0.0001109484,0.0002111084,0.0004027408,0.0001656079,0.0003182676,0.0001396847,0.0002764266,0.0001312412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001325828,"about_ca_system_score_gemma":0.0008243124,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1485575,"about_ca_topic_score_gemma":0.09554776,"domain_scores_codex":[0.9999115,0.00001881169,0.000004942069,0.00001640458,0.00003459505,0.00001378383],"domain_scores_gemma":[0.9998353,0.00006466499,0.00001930303,0.0000077847,0.00006585109,0.000007126263],"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":[0.00008165911,0.00003753116,0.00855941,0.00002249752,0.00002225748,0.0001014359,0.00003763984,0.9699833,0.001425796,0.001358993,0.0006242894,0.01774511],"study_design_scores_gemma":[0.000001419003,0.000004816807,0.001139356,6.811075e-7,0.000001851619,0.000003150106,0.000002784603,0.9985642,0.0001276528,0.00009292854,0.00005997995,0.000001199449],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9105534,0.0001308561,0.08237631,0.0002837281,0.00003170558,0.00002588924,0.0002763985,0.0001335554,0.006188279],"genre_scores_gemma":[0.9943933,0.00005316885,0.00381879,0.000006691015,0.000004244846,0.000009164252,0.0001371988,0.000004059397,0.001573225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8514425,"threshold_uncertainty_score":0.2953856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04233742099055166,"score_gpt":0.205533934489411,"score_spread":0.1631965134988594,"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."}}