{"id":"W7145955814","doi":"","title":"信号制御の最適化におけるメタ戦略の比較と制御パラメータの連続自動調整への適用","year":2006,"lang":"ja","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Internet of Things and Social Network Interactions","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alpha Technologies (Canada)","funders":"","keywords":"Offset (computer science); Metaheuristic; Genetic algorithm; Simulated annealing; Optimal control; Control point; Control (management)","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":[0.0008079665,0.0004831932,0.0005351842,0.0008267904,0.0003892476,0.0009097575,0.0005079734,0.0004969377,0.001491228],"category_scores_gemma":[0.001599579,0.0002166783,0.0003772804,0.0008584723,0.0005147863,0.0008415675,0.0003187344,0.0003882859,0.0004774682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005001132,"about_ca_system_score_gemma":0.0009359185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001800055,"about_ca_topic_score_gemma":0.002081854,"domain_scores_codex":[0.9995756,0.00009224851,0.00002947006,0.0001086467,0.0001621838,0.00003191509],"domain_scores_gemma":[0.9994221,0.000283252,0.0001194897,0.00004926197,0.0001008475,0.00002514458],"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":[0.0001015661,0.00008772263,0.002462899,0.0003336297,0.00005592653,0.00009132852,0.0001010856,0.4936287,0.02866823,0.01707487,0.0009790844,0.456415],"study_design_scores_gemma":[0.00004371411,0.0003148659,0.002435778,0.00004646071,0.00004881129,0.0003707378,0.0001222872,0.9517351,0.02037508,0.01293223,0.01152574,0.00004921101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02673796,0.000992112,0.9651037,0.0001552016,0.00005717297,0.00005228061,0.00003264801,0.0002560326,0.006612863],"genre_scores_gemma":[0.4896995,0.001437387,0.502783,0.00009442817,0.00009780828,0.0001622454,0.0001011182,0.0001830338,0.005441471],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001800055,"threshold_uncertainty_score":0.004988611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01213788230153902,"score_gpt":0.2505709440155723,"score_spread":0.2384330617140333,"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."}}