{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006286359,0.0007721132,0.0007082398,0.001086953,0.0004321921,0.001007844,0.001143771,0.0007637452,0.0009071723],"category_scores_gemma":[0.02510838,0.0003328802,0.0007373253,0.001895632,0.0005786022,0.002833815,0.0005117821,0.001343012,0.0002208947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005915268,"about_ca_system_score_gemma":0.0006361121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01068446,"about_ca_topic_score_gemma":0.005014529,"domain_scores_codex":[0.9979585,0.001081492,0.000131044,0.0003404157,0.0003320623,0.0001564318],"domain_scores_gemma":[0.9816257,0.0132444,0.001249388,0.001902628,0.001786577,0.0001913192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003740628,0.0004409009,0.2478218,0.0002679494,0.0003192529,0.0005220097,0.0005661244,0.6347705,0.002357396,0.009012422,0.003166407,0.1003812],"study_design_scores_gemma":[0.000005123853,0.00009409458,0.01708988,0.00001535356,0.00003256191,0.00007669441,0.0001349631,0.9801868,0.0006423566,0.001248296,0.000457729,0.00001624078],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9436992,0.0006786793,0.05320555,0.0003180641,0.00003492149,0.0000424667,0.000282368,0.0002814223,0.001457446],"genre_scores_gemma":[0.9926731,0.0002246342,0.006447912,0.00002442688,0.00001988461,0.00001713761,0.0003885502,0.00001709038,0.0001872003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01068446,"threshold_uncertainty_score":0.0332458,"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."}}