{"id":"W4313644256","doi":"10.1371/journal.pone.0279572","title":"A novel hybrid PSO based on levy flight and wavelet mutation for global optimization","year":2023,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Optical Wireless Communication Technologies","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Polit National Laboratory for Marine Science and Technology; National Natural Science Foundation of China","keywords":"Lévy flight; Mutation; Wavelet; Computer science; Particle swarm optimization; Computational biology; Biology; Genetics; Artificial intelligence; Mathematics; Algorithm; Statistics","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":[0.00006055612,0.00008090302,0.0001059308,0.00006968924,0.00004821026,0.00002893996,0.000108401,0.00005266427,0.000005568783],"category_scores_gemma":[0.0002159846,0.00008724122,0.00001623942,0.0002238504,0.00002642677,0.00006324607,0.00002856234,0.00006164388,0.00001840242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005682777,"about_ca_system_score_gemma":0.000006188085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001036421,"about_ca_topic_score_gemma":0.000001424921,"domain_scores_codex":[0.9995227,0.00000533104,0.000117169,0.0001089883,0.0001168805,0.0001289552],"domain_scores_gemma":[0.9995496,0.0001267212,0.00001789116,0.0002342951,0.00004610445,0.00002538999],"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":[0.0000458073,0.0006011811,0.0001402474,0.0004654122,0.0001458632,0.000002973413,0.00004946653,0.9475356,0.0169177,0.0104023,0.0006826099,0.02301086],"study_design_scores_gemma":[0.0003848332,0.00005253131,0.0003621269,0.00005628186,0.00001532287,3.624693e-7,0.00001295648,0.9643818,0.03420999,0.0003895769,0.00003957752,0.00009461666],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.281271,0.0001132221,0.7076694,0.003716858,0.00006042752,0.0008295044,0.0001849128,0.004182932,0.001971765],"genre_scores_gemma":[0.8612908,0.00007982314,0.1382797,0.00004331186,0.00001251584,0.00012129,0.0001292596,0.00001976372,0.00002355323],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5800198,"threshold_uncertainty_score":0.3557594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04174763809861262,"score_gpt":0.2302234605513735,"score_spread":0.1884758224527609,"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."}}