{"id":"W2534400317","doi":"","title":"Model order reduction using PSO algorithm and it's application to power systems","year":2009,"lang":"en","type":"article","venue":"International Conference on Electric Power and Energy Conversion Systems","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Electric power system; Reduction (mathematics); Particle swarm optimization; Computer science; Mathematical optimization; Nonlinear system; Power (physics); Control theory (sociology); Algorithm; Mathematics; Artificial intelligence","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":[0.0002880924,0.0004576081,0.0007061451,0.0003651327,0.000295539,0.0004927861,0.0002661227,0.000409845,0.001224153],"category_scores_gemma":[0.000927864,0.0002125349,0.0006481249,0.0004958076,0.0002842046,0.0004355944,0.0002955903,0.0006165587,0.0002142039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002284165,"about_ca_system_score_gemma":0.0004960229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004626656,"about_ca_topic_score_gemma":0.002192979,"domain_scores_codex":[0.9998422,0.00005632818,0.000009025202,0.00002029149,0.00006151822,0.00001062065],"domain_scores_gemma":[0.9998088,0.0001001033,0.00002270336,0.00002191946,0.00003867604,0.000007826859],"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":[0.00002458719,0.00002739529,0.0004168337,0.0001124208,0.00003850191,0.0000919427,0.00006680062,0.8898588,0.003935367,0.01141416,0.001199245,0.09281403],"study_design_scores_gemma":[0.000003531209,0.00001408925,0.00007264477,0.000003176763,0.000003385067,0.00002010644,0.00000373202,0.9966003,0.0003834847,0.002184627,0.0007077454,0.000003185852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00743007,0.0003380387,0.9892034,0.0001346444,0.00004829855,0.00002508072,0.0000163049,0.0002601862,0.00254395],"genre_scores_gemma":[0.6193799,0.001121804,0.3738116,0.00009908398,0.00009887123,0.0001990672,0.000143741,0.0001656189,0.004980396],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004626656,"threshold_uncertainty_score":0.00919944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02122806948776572,"score_gpt":0.2676946429150235,"score_spread":0.2464665734272578,"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."}}