{"id":"W4379231583","doi":"10.23977/cpcs.2023.070108","title":"Cell base station traffic prediction based on GRU","year":2023,"lang":"en","type":"article","venue":"Computing Performance and Communication systems","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Autoregressive integrated moving average; Base station; Artificial neural network; Computer science; Data mining; Traffic generation model; Convolutional neural network; Base (topology); Network traffic simulation; Time series; Real-time computing; Artificial intelligence; Simulation; Network traffic control; Computer network; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003942373,0.0001015237,0.00009459519,0.0002246261,0.000203457,0.00006747101,0.0001434967,0.00005011391,0.000001333002],"category_scores_gemma":[0.000003240429,0.0001069249,0.00001890886,0.0003104114,0.00002046849,0.0001272175,0.00003009804,0.0001294664,0.00004238697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003891326,"about_ca_system_score_gemma":0.000006099316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002991506,"about_ca_topic_score_gemma":5.446723e-7,"domain_scores_codex":[0.9993407,0.00004925071,0.0002251172,0.0001142784,0.0001379185,0.0001326987],"domain_scores_gemma":[0.99947,0.00005860244,0.00004558597,0.0003594781,0.00002901447,0.00003730098],"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":[0.000004489896,0.00001565393,0.000699738,0.0001852948,0.000005364378,2.155623e-7,0.000298509,0.9410135,0.00005017806,0.0001063874,0.03522648,0.02239414],"study_design_scores_gemma":[0.0002687963,0.00004702158,0.007152295,0.0001531062,0.000005946045,8.025913e-7,0.0002139011,0.9824102,0.00007971189,8.338243e-7,0.009576229,0.00009119271],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9470692,0.000240461,0.03404396,0.0000764841,0.0004493119,0.0004003874,0.00001196301,0.01030288,0.007405401],"genre_scores_gemma":[0.998727,0.0006257838,0.0002964078,0.00003768936,0.00003741079,0.00003958874,0.0001476755,0.00001880442,0.00006960594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05165787,"threshold_uncertainty_score":0.4360272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01469243258691223,"score_gpt":0.2113310743769374,"score_spread":0.1966386417900251,"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."}}