{"id":"W2060355705","doi":"10.1504/ijica.2011.039593","title":"Particle swarm optimisation with simple and efficient neighbourhood search strategies","year":2011,"lang":"en","type":"article","venue":"International Journal of Innovative Computing and Applications","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"National Natural Science Foundation of China","keywords":"Particle swarm optimization; Neighbourhood (mathematics); Computer science; Locality; Mathematical optimization; Benchmark (surveying); Simple (philosophy); Local search (optimization); Swarm behaviour; Algorithm; Artificial intelligence; Mathematics","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":[0.0008719611,0.0007057253,0.00121536,0.0005903339,0.000341497,0.0007335134,0.001041751,0.001085283,0.0008688403],"category_scores_gemma":[0.001976887,0.0003579828,0.0008130717,0.0008717062,0.0005579936,0.000895521,0.001007119,0.0006194235,0.0004863446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002919573,"about_ca_system_score_gemma":0.0005549719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001506983,"about_ca_topic_score_gemma":0.001502268,"domain_scores_codex":[0.9992106,0.0002422058,0.00005000463,0.00008417943,0.0003772074,0.00003571449],"domain_scores_gemma":[0.9996376,0.0001443576,0.00005989824,0.00005876576,0.0000804223,0.00001893348],"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":[0.00009772198,0.0001008791,0.0008106906,0.0002934189,0.000137803,0.0002142294,0.0001183111,0.8046001,0.01069975,0.02457308,0.001948486,0.1564055],"study_design_scores_gemma":[0.00008290628,0.0001232539,0.0003907946,0.0000159242,0.00003145876,0.0001244264,0.00001097451,0.9824535,0.002205764,0.008327523,0.006210966,0.00002246499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01479349,0.000761741,0.9788344,0.00009062203,0.0000787003,0.0001126062,0.00003136064,0.0002258929,0.005071086],"genre_scores_gemma":[0.4086877,0.001234247,0.5808642,0.0001225673,0.0001219354,0.0004868267,0.0001859953,0.0001003861,0.008196119],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001506983,"threshold_uncertainty_score":0.004611373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03848668812058931,"score_gpt":0.3250332525350805,"score_spread":0.2865465644144912,"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."}}