{"id":"W4411037248","doi":"10.18280/jesa.580405","title":"SVM and ELM Based on Binary Grey Wolf Optimization for Feature Selection to Detect Defaults of Grid-Connected PV Systems Under MPPT Mode","year":2025,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Support vector machine; Mode (computer interface); Feature selection; Computer science; Extreme learning machine; Selection (genetic algorithm); Grid; Default; Binary number; Photovoltaic system; Artificial intelligence; Feature (linguistics); Pattern recognition (psychology); Engineering; Mathematics; Operating system; Business","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":[0.001133672,0.000545034,0.0008300747,0.0009469778,0.0002238883,0.0006690386,0.0005678997,0.0006753722,0.0008817003],"category_scores_gemma":[0.002544954,0.000236737,0.000535647,0.0006416567,0.000282843,0.0006399457,0.0004853415,0.0006781133,0.0002324019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000302885,"about_ca_system_score_gemma":0.0004026402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001239756,"about_ca_topic_score_gemma":0.0007350045,"domain_scores_codex":[0.9994185,0.0002001531,0.00004984172,0.0001147271,0.0001642625,0.00005250026],"domain_scores_gemma":[0.9992138,0.0004443635,0.00008270203,0.00004933868,0.0001834909,0.00002629856],"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":[0.0003651455,0.000223573,0.006936831,0.0001309835,0.0001664135,0.0001250719,0.00009212465,0.4928896,0.009420451,0.003561028,0.001757278,0.4843314],"study_design_scores_gemma":[0.000005063494,0.00003156386,0.0007290334,0.000003110495,0.00000493635,0.00001182814,0.000004940321,0.9980004,0.0006613522,0.0004500294,0.00009491948,0.000002889944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1067819,0.0004303097,0.8902823,0.000186454,0.00004674562,0.00005358931,0.00005825809,0.0006782084,0.001482277],"genre_scores_gemma":[0.8962071,0.00009868971,0.1018907,0.00008591427,0.00003117805,0.0001024942,0.0001462218,0.00003780684,0.001399921],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001239756,"threshold_uncertainty_score":0.005995452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01240108791634774,"score_gpt":0.265598366179752,"score_spread":0.2531972782634043,"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."}}