{"id":"W2182988819","doi":"10.32920/ryerson.14649354.v1","title":"Chaotic time series forecasting with residual analysis using synergy of ensemble neural networks and Taguchi's design of experiments","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Chaotic; Residual; Artificial neural network; Computer science; Series (stratigraphy); Time series; Embedding; Phase space; Algorithm; Mathematical optimization; Artificial intelligence; Mathematics; Machine learning","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":[0.008875763,0.0012156,0.001573591,0.001115285,0.0004660553,0.0008692482,0.001046815,0.0008712549,0.0007275292],"category_scores_gemma":[0.006708091,0.0005141273,0.001610254,0.001006751,0.000531245,0.0007874618,0.0005522502,0.0009786143,0.00007680463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000806404,"about_ca_system_score_gemma":0.001001084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001388073,"about_ca_topic_score_gemma":0.001426927,"domain_scores_codex":[0.9962636,0.00182161,0.0003593752,0.0004548047,0.0009185071,0.0001821439],"domain_scores_gemma":[0.9967653,0.001930288,0.0003695402,0.0003428877,0.0005340101,0.00005802535],"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":[0.001203528,0.001096539,0.005834399,0.001479543,0.0004887697,0.0001280953,0.0004379881,0.6405807,0.1193407,0.01019134,0.0003193735,0.218899],"study_design_scores_gemma":[0.000114854,0.002600855,0.002902394,0.00005554911,0.0002482634,0.00003586226,0.00007196518,0.9218667,0.06842422,0.002419068,0.001180475,0.00007970622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1346032,0.0004640337,0.8621197,0.00005153177,0.00009909619,0.001023502,0.00005634303,0.0002819966,0.001300751],"genre_scores_gemma":[0.4873596,0.0004301353,0.5094463,0.00003422948,0.00001956906,0.0022104,0.00006301569,0.00002205129,0.000414759],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008875763,"threshold_uncertainty_score":0.04694003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04901470887794573,"score_gpt":0.2585273144339447,"score_spread":0.209512605555999,"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."}}