{"id":"W2786922041","doi":"10.1109/ssci.2017.8280938","title":"Differential evolution with center-based mutation for large-scale optimization","year":2017,"lang":"en","type":"article","venue":"","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Benchmark (surveying); Differential evolution; Mutation; Crossover; Mathematical optimization; Convergence (economics); Dimension (graph theory); Scheme (mathematics); Computer science; Optimization problem; Algorithm; Mathematics; Artificial intelligence; Mathematical analysis","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":[0.00115515,0.0006658552,0.0008415531,0.0006730744,0.0003677936,0.0004721795,0.001089868,0.0007376113,0.0006462698],"category_scores_gemma":[0.002027727,0.0002704462,0.0006151379,0.001028445,0.0008308332,0.0005798559,0.0009210703,0.0008678925,0.0001330219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006788795,"about_ca_system_score_gemma":0.0006435249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00165642,"about_ca_topic_score_gemma":0.001010705,"domain_scores_codex":[0.9995332,0.000145081,0.00002179248,0.00005554068,0.0002158785,0.00002851327],"domain_scores_gemma":[0.9994306,0.0003134997,0.00006598767,0.00006487739,0.0001032617,0.00002168994],"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":[0.00003678602,0.00004117738,0.0004178602,0.00007869645,0.00005451616,0.0001000266,0.00005344939,0.8960896,0.00768836,0.02454007,0.0005384495,0.07036108],"study_design_scores_gemma":[0.000007960703,0.0000198158,0.00006110745,0.000002266322,0.00000494099,0.00001829857,0.00000190571,0.9962499,0.0008372291,0.002227953,0.0005649416,0.000003691188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01389015,0.0004414141,0.9837458,0.00006893123,0.00003717589,0.00004466216,0.00000929838,0.0002204538,0.001542098],"genre_scores_gemma":[0.5980078,0.000637203,0.3988141,0.00008644635,0.00005116289,0.0002707524,0.00006192731,0.00007712888,0.001993459],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00165642,"threshold_uncertainty_score":0.006109118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02018209671631591,"score_gpt":0.2914879912554281,"score_spread":0.2713058945391122,"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."}}