{"id":"W334654498","doi":"10.1007/978-1-4614-3442-9_8","title":"Time-Series Forecasting via Complex Fuzzy Logic","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Series (stratigraphy); Computer science; Chaotic; Window (computing); Fuzzy logic; Time series; Artificial neural network; Computation; Adaptive neuro fuzzy inference system; Inference; Sliding window protocol; Data mining; Algorithm; Artificial intelligence; Fuzzy control system; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003264388,0.0004705705,0.000712424,0.0001172592,0.0001834506,0.0002084035,0.001393877,0.0003331963,0.0003549282],"category_scores_gemma":[0.00001910448,0.0003665744,0.0002495293,0.00003850228,0.0001384055,0.0001836035,0.0004988392,0.0002573657,0.003546955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005637729,"about_ca_system_score_gemma":0.00004968815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002100439,"about_ca_topic_score_gemma":0.00001421018,"domain_scores_codex":[0.9978958,0.00003611722,0.0005117445,0.0007077149,0.0004275129,0.0004210542],"domain_scores_gemma":[0.9983159,0.0001304045,0.000332917,0.0009325704,0.0001430714,0.0001451633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000004351088,0.000003455895,0.000001087745,0.00002828951,0.00003730533,0.00002949231,0.00002743736,0.00001498208,0.00003046005,0.9636144,0.01129869,0.02491006],"study_design_scores_gemma":[0.0002833818,0.0002587087,0.00000724133,0.00008410665,0.00002120804,0.0002054318,0.000002430185,0.02322316,0.000003328446,0.6243885,0.3507938,0.0007287461],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[2.871746e-7,0.0001719414,0.2173078,0.0004984206,0.0003739535,0.0002377913,0.00000329582,0.0004020028,0.7810045],"genre_scores_gemma":[0.005283347,0.000008116639,0.02072152,0.001297743,0.000686003,0.00001575746,0.00002351757,0.00004110257,0.9719229],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3394951,"threshold_uncertainty_score":0.9998786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04314150426978685,"score_gpt":0.2105247391292204,"score_spread":0.1673832348594335,"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."}}