{"id":"W2027723026","doi":"10.1117/12.542156","title":"Self-adaptive parameters in genetic algorithms","year":2004,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières; Defence Research and Development Canada","funders":"","keywords":"Computer science; Algorithm; Genetic algorithm; Quality control and genetic algorithms; Context (archaeology); Range (aeronautics); Set (abstract data type); Chromosome; Resolution (logic); Artificial intelligence; Meta-optimization; Machine learning","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":[0.001694039,0.0007167762,0.0009244133,0.000928383,0.0004832043,0.001504088,0.001514945,0.001799034,0.001389988],"category_scores_gemma":[0.008281578,0.0005123949,0.0005340447,0.001221943,0.001698599,0.0019525,0.001048106,0.001822699,0.0005833357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000977383,"about_ca_system_score_gemma":0.0006828213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001598028,"about_ca_topic_score_gemma":0.001101866,"domain_scores_codex":[0.9988887,0.000497258,0.00005710415,0.000171398,0.0003336351,0.00005182916],"domain_scores_gemma":[0.9978977,0.00133813,0.0002038209,0.0002626608,0.0002578332,0.00003986061],"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":[0.00003708271,0.00004602198,0.0008829485,0.0001073152,0.00006668425,0.00007972508,0.0002023421,0.812044,0.003182608,0.09534838,0.0012981,0.08670481],"study_design_scores_gemma":[0.00003306469,0.00004935315,0.0002248341,0.0000687346,0.00002900287,0.00008668441,0.00004078267,0.8919095,0.002079183,0.09497979,0.0104606,0.00003846986],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01000594,0.001639334,0.9796726,0.0002965408,0.00008588972,0.000105709,0.0000325995,0.000418736,0.007742659],"genre_scores_gemma":[0.4392048,0.002415576,0.5520957,0.0004640091,0.0001491494,0.0005458545,0.0001044568,0.0003055442,0.004714868],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001799034,"threshold_uncertainty_score":0.008959055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01612470005081351,"score_gpt":0.2451938951826961,"score_spread":0.2290691951318826,"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."}}