{"id":"W4285813782","doi":"10.1109/iwcmc55113.2022.9825059","title":"An Empirical Study on Internet Traffic Prediction Using Statistical Rolling Model","year":2022,"lang":"en","type":"article","venue":"2022 International Wireless Communications and Mobile Computing (IWCMC)","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Autoregressive integrated moving average; Exponential smoothing; Mean absolute percentage error; Akaike information criterion; Computer science; Internet traffic; Mean squared prediction error; Data mining; The Internet; Statistics; Time series; Artificial neural network; Machine learning; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004193715,0.0001676811,0.0001652675,0.0002651956,0.0004267062,0.0001057999,0.0007442099,0.00003741414,0.0000325091],"category_scores_gemma":[0.000006356042,0.0001970607,0.00004112257,0.0001677602,0.00005910741,0.0001307926,0.0005275765,0.0005116813,0.000001846964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002458161,"about_ca_system_score_gemma":0.00002086466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001894211,"about_ca_topic_score_gemma":0.00001106172,"domain_scores_codex":[0.9986352,0.0001665445,0.0003942861,0.0002889887,0.0003459828,0.0001689558],"domain_scores_gemma":[0.9991252,0.000110955,0.00006678482,0.0005665302,0.00005241406,0.00007814039],"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":[0.00001827985,0.0007358892,0.001391761,0.000006900894,0.0000907391,0.000002938287,0.001941304,0.9617684,0.0002447651,0.001605295,0.00172165,0.03047203],"study_design_scores_gemma":[0.0003794085,0.0003036765,0.001340431,0.00001547563,0.00002686589,0.00001205857,0.001764824,0.993212,0.00001135871,0.0000350818,0.002738847,0.0001599762],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7304695,0.00006777393,0.2667902,0.00004711653,0.0003245828,0.0003870491,0.00007034578,0.001342576,0.0005009577],"genre_scores_gemma":[0.9964066,0.00008898573,0.002876986,0.00009444785,0.00005338515,0.0001487469,0.000265334,0.00003824839,0.00002724652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2659372,"threshold_uncertainty_score":0.8035901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03504430023944216,"score_gpt":0.3247969791013108,"score_spread":0.2897526788618686,"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."}}