{"id":"W4407920596","doi":"10.18280/jesa.580101","title":"Three-Level Boost Converter with Fuzzy Logic for PV-Battery Energy Systems in DC Voltage Control","year":2025,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Advanced DC-DC Converters","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Boost converter; Fuzzy logic; Battery (electricity); Ćuk converter; Flyback converter; Voltage; Forward converter; Computer science; Electrical engineering; Control theory (sociology); Control (management); Engineering; Physics; Power (physics); Artificial intelligence","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":[0.0001923813,0.0002735782,0.0002384564,0.0002440992,0.000353615,0.0006736272,0.0004443132,0.0003250662,0.002171622],"category_scores_gemma":[0.0002348793,0.0001072001,0.0002588249,0.0003516275,0.0001478358,0.0002800609,0.0001800122,0.0005633907,0.0005231862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003421,"about_ca_system_score_gemma":0.0003591298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002512247,"about_ca_topic_score_gemma":0.002704694,"domain_scores_codex":[0.9998465,0.00002279121,0.00000925509,0.00002380035,0.0000850151,0.00001267313],"domain_scores_gemma":[0.9999396,0.00001500515,0.000005442279,0.000007363733,0.0000291176,0.000003449374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002628886,0.0002577901,0.001537188,0.0008605524,0.00008703016,0.0004973158,0.0003261334,0.1658939,0.1360715,0.03742675,0.004243235,0.6525356],"study_design_scores_gemma":[0.00005521146,0.0004329526,0.00176054,0.0001047753,0.00007228977,0.0004831289,0.00007258724,0.8998257,0.05186972,0.01604076,0.02923979,0.00004248149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03137057,0.001771579,0.9367678,0.0001877193,0.0001742413,0.000145739,0.00007722184,0.001476564,0.02802849],"genre_scores_gemma":[0.8953283,0.000793468,0.09491482,0.0001348116,0.00004458114,0.0001053076,0.00007256835,0.00003656012,0.008569589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002512247,"threshold_uncertainty_score":0.007264853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01555863218076697,"score_gpt":0.2260782902516264,"score_spread":0.2105196580708594,"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."}}