{"id":"W3001996239","doi":"10.20944/preprints202001.0312.v1","title":"Hybrid Model of Singular Value Decomposition, ANFIS and Genetic Algorithm for Prediction of Sediment Transport in Sewers","year":2020,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Université Laval","funders":"","keywords":"Adaptive neuro fuzzy inference system; Dimensionless quantity; Singular value decomposition; Genetic algorithm; Mathematics; Froude number; Algorithm; Particle swarm optimization; Applied mathematics; Mathematical optimization; Computer science; Fuzzy logic; Geometry; Artificial intelligence; Mechanics; Physics; Fuzzy control system; Flow (mathematics)","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":[0.0004597312,0.0007577759,0.0007988582,0.0005061754,0.0004458686,0.0008381527,0.0007539816,0.001135754,0.0009169386],"category_scores_gemma":[0.0008007815,0.0003951261,0.0007452921,0.0004458869,0.0003364338,0.000532517,0.0003760431,0.0007172166,0.0001489928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006296757,"about_ca_system_score_gemma":0.0007940272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02323936,"about_ca_topic_score_gemma":0.01408438,"domain_scores_codex":[0.9997856,0.00005177616,0.00001905778,0.00004994145,0.00006495672,0.00002866488],"domain_scores_gemma":[0.9997481,0.0001304656,0.00003380193,0.000008507725,0.00006857576,0.00001055722],"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":[0.0000443995,0.00003127079,0.0008887136,0.00003482571,0.00003498931,0.00006984522,0.0000315318,0.9874277,0.00125651,0.0005229468,0.0001394388,0.009517866],"study_design_scores_gemma":[0.000001846935,0.00001579815,0.0001100136,0.000002090905,0.000003484445,0.000003559491,0.000003322655,0.9995926,0.0001270497,0.00009254668,0.0000459864,0.000001681107],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3047223,0.001232988,0.6832239,0.0003910236,0.0001557078,0.0001398967,0.0001782568,0.001034251,0.008921624],"genre_scores_gemma":[0.9709036,0.0003052507,0.02561376,0.00003765558,0.00002193255,0.0001257814,0.0001135085,0.00001466924,0.002863907],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02323936,"threshold_uncertainty_score":0.0462082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06986102980649314,"score_gpt":0.2950073153001462,"score_spread":0.2251462854936531,"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."}}