{"id":"W2322542903","doi":"10.2316/journal.203.2011.2.203-4835","title":"HEURISTIC JUSTIFICATION AND DIFFERENTIAL EVOLUTION-BASED FINAL SELF-RESTORATION STATE OPTIMIZATION FOR URBAN POWER GRID AFTER BLACKOUT","year":2011,"lang":"en","type":"article","venue":"International Journal of Power and Energy Systems","topic":"Power Systems and Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Blackout; Differential evolution; Heuristic; Grid; Mathematical optimization; Electric power system; Computer science; Power (physics); Power grid; Differential (mechanical device); State (computer science); Reliability engineering; Operations research; Engineering; Mathematics; Algorithm","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006712414,0.0003465242,0.0005309079,0.0004780463,0.0003314394,0.0005233692,0.0004888025,0.0005110812,0.001194822],"category_scores_gemma":[0.001228939,0.0002521249,0.0003698208,0.0003025491,0.0005461033,0.0004311915,0.0005081435,0.0003431822,0.00006126298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006487212,"about_ca_system_score_gemma":0.0007567699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004868605,"about_ca_topic_score_gemma":0.004280523,"domain_scores_codex":[0.9998024,0.0000832672,0.000008232117,0.00002623257,0.00004606251,0.00003389926],"domain_scores_gemma":[0.9996297,0.0002046119,0.00005198686,0.0000249129,0.00006738875,0.00002128988],"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":[0.00003615618,0.00001788208,0.0004817502,0.00002214914,0.00001327963,0.0000378308,0.00003526989,0.9780539,0.0007326325,0.005414008,0.0002752002,0.01487996],"study_design_scores_gemma":[0.000005983815,0.00001308159,0.00006972328,0.000002145861,0.00000254908,0.000003922755,0.000005945981,0.9986296,0.0001570257,0.0009741063,0.0001343115,0.000001657995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1723248,0.0002385518,0.8190865,0.0003118388,0.00003972585,0.00008666511,0.00004189373,0.0002473113,0.007622749],"genre_scores_gemma":[0.9421358,0.00005850176,0.05605774,0.00003904319,0.000006787789,0.00006570376,0.00004477562,0.00002108284,0.001570651],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004868605,"threshold_uncertainty_score":0.00968051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009204178229971854,"score_gpt":0.1919916464617682,"score_spread":0.1827874682317963,"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."}}