{"id":"W2105720696","doi":"10.1504/ijmic.2012.045693","title":"Machine vibration prediction using ANFIS and wavelet packet decomposition","year":2012,"lang":"en","type":"article","venue":"International Journal of Modelling Identification and Control","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Syncrude","keywords":"Adaptive neuro fuzzy inference system; Wavelet packet decomposition; Wavelet; SIGNAL (programming language); Computer science; Vibration; Series (stratigraphy); Decomposition; Fuzzy logic; Artificial intelligence; Wavelet transform; Fuzzy control system; Acoustics; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005296645,0.0005722418,0.000728057,0.0005095566,0.0002220481,0.0004114076,0.0004694148,0.0005959592,0.0007225461],"category_scores_gemma":[0.001079683,0.0003347771,0.0005882532,0.0004128166,0.0002009463,0.0006862633,0.0002521475,0.0007486758,0.0002399814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000294673,"about_ca_system_score_gemma":0.0003258068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005596853,"about_ca_topic_score_gemma":0.003996805,"domain_scores_codex":[0.9997285,0.00005708685,0.00002088079,0.0000504676,0.0001241904,0.00001893481],"domain_scores_gemma":[0.9997665,0.0001272206,0.0000272042,0.00001866927,0.00005312626,0.000007228855],"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":[0.00008589243,0.00006188748,0.001009057,0.0001191621,0.00009296296,0.0001106365,0.00005301751,0.8211687,0.009557289,0.002841039,0.0007672242,0.1641332],"study_design_scores_gemma":[0.000001721394,0.000009130777,0.0001167751,0.000002450354,0.000003601447,0.000005820759,0.000001828934,0.9988746,0.0005305564,0.0003025527,0.0001491304,0.00000185457],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02312575,0.0002694337,0.9746137,0.00007726668,0.0000502923,0.0000259758,0.00005153672,0.0007364634,0.001049564],"genre_scores_gemma":[0.7342074,0.0005477809,0.2621478,0.00004500017,0.00004438932,0.0001295153,0.0002177159,0.00006024537,0.002600122],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005596853,"threshold_uncertainty_score":0.01112854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02100117685958766,"score_gpt":0.2741690787959654,"score_spread":0.2531679019363777,"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."}}