{"id":"W2154823988","doi":"10.1109/tap.2010.2050425","title":"A Hybrid Optimization Algorithm and Its Application for Conformal Array Pattern Synthesis","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Antennas and Propagation","topic":"Antenna Design and Optimization","field":"Engineering","cited_by":123,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Particle swarm optimization; Conformal map; Algorithm; Conformal antenna; Antenna array; Genetic algorithm; Fitness function; Computer science; Evolutionary algorithm; Antenna (radio); Hybrid algorithm (constraint satisfaction); Mathematical optimization; Topology (electrical circuits); Mathematics; Microstrip antenna; Telecommunications","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":[0.0004560361,0.0005079919,0.0005267958,0.0004939217,0.0001969713,0.000509534,0.0004646245,0.0006882925,0.001182796],"category_scores_gemma":[0.0008933638,0.0002837419,0.000520057,0.0005895655,0.0003993339,0.0004868481,0.0005225714,0.0005070961,0.0002675683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002258897,"about_ca_system_score_gemma":0.0002688248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006820643,"about_ca_topic_score_gemma":0.0005198821,"domain_scores_codex":[0.9997752,0.00006996522,0.00001111791,0.00003600725,0.00009093172,0.00001676025],"domain_scores_gemma":[0.9997771,0.0001266463,0.00001941726,0.00002539314,0.00004304976,0.000008360259],"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":[0.00004578548,0.00003457701,0.0004793899,0.00008484147,0.00006608746,0.00007859075,0.00006249765,0.7928787,0.01417208,0.02369117,0.0008886966,0.1675175],"study_design_scores_gemma":[0.000008051682,0.00002948102,0.00007314591,0.000003890454,0.000005838643,0.00004310854,0.000004870903,0.9944023,0.001745065,0.002002061,0.001677092,0.00000514464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005105854,0.0001244857,0.9927964,0.0000416631,0.00001839057,0.00001416647,0.000006959577,0.0001113015,0.001780821],"genre_scores_gemma":[0.2338844,0.0003246102,0.7623877,0.00008204012,0.00003408925,0.0001773981,0.00005172967,0.00007145145,0.002986541],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001182796,"threshold_uncertainty_score":0.003956854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00727345264757536,"score_gpt":0.1985037124664831,"score_spread":0.1912302598189077,"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."}}