{"id":"W4410738454","doi":"10.1109/iraset64571.2025.11008199","title":"Comparison of the Genetic Algorithm and the Particle Swarm Optimization for Minimizing Fuel Consumption for UAVs","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Aircraft Design and Technologies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Particle swarm optimization; Genetic algorithm; Fuel efficiency; Computer science; Mathematical optimization; Consumption (sociology); Algorithm; Engineering; Mathematics; Automotive engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008127002,0.0000491666,0.00008655898,0.000005621108,0.0001232717,0.0000104487,0.0001105737,0.00003050061,0.00001720418],"category_scores_gemma":[0.00007260463,0.00002685379,0.00003050646,0.00007648362,0.0003373025,0.00004094747,0.00007589948,0.00002496789,7.2259e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000169956,"about_ca_system_score_gemma":0.000002879931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008342183,"about_ca_topic_score_gemma":0.000008907276,"domain_scores_codex":[0.9995996,0.00001522546,0.0001334731,0.0001095706,0.00005110991,0.00009107147],"domain_scores_gemma":[0.9995855,0.0002221657,0.00005282363,0.0001248207,0.000007202709,0.00000747372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002571729,0.0001847216,0.1105836,0.0001422301,0.00005291468,7.027509e-8,0.0008743492,0.3038614,0.00662579,0.02041312,0.00200923,0.5549954],"study_design_scores_gemma":[0.001108546,0.00003177388,0.007450717,0.000009116148,0.00003048214,2.945693e-7,0.0003613798,0.9374738,0.0417434,0.01107809,0.0006632741,0.00004916345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03921552,0.0002656787,0.9586081,0.0009588331,0.00004668262,0.0007085667,0.000003181096,0.00003055835,0.0001629057],"genre_scores_gemma":[0.7375053,0.00004850073,0.2619924,0.0001057919,0.000002713898,0.0001041296,6.343064e-7,0.000002805808,0.0002376871],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6982898,"threshold_uncertainty_score":0.1242805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02374149451471219,"score_gpt":0.2942674264681193,"score_spread":0.2705259319534071,"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."}}