{"id":"W4392905317","doi":"10.1109/rams51492.2024.10457834","title":"A New Maintenance Plan for Wind Turbine Farms Using Reinforcement Learning","year":2024,"lang":"en","type":"article","venue":"","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Reinforcement learning; Plan (archaeology); Turbine; Reinforcement; Computer science; Wind power; Engineering; Marine engineering; Artificial intelligence; Electrical engineering; Structural engineering; Mechanical engineering; Geology","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":[0.0004831301,0.0006130309,0.0006181228,0.0005551576,0.0003837108,0.0006347199,0.0008947968,0.0006893382,0.002055544],"category_scores_gemma":[0.001333604,0.0003205414,0.0003669845,0.0003013366,0.000305523,0.0008185141,0.0005060842,0.0006533973,0.0002299557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007605927,"about_ca_system_score_gemma":0.001329045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007248613,"about_ca_topic_score_gemma":0.008142562,"domain_scores_codex":[0.999795,0.000034198,0.00001195821,0.00006105559,0.0000551696,0.00004266275],"domain_scores_gemma":[0.99959,0.0001402315,0.00008725872,0.0000255775,0.00009885115,0.00005808948],"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":[0.00005925511,0.00006218986,0.001086721,0.00003504681,0.00001614152,0.0001098855,0.00003690448,0.9544373,0.001353111,0.002113269,0.000737457,0.03995273],"study_design_scores_gemma":[0.000009413377,0.00002359668,0.0001172411,0.000003464488,0.000003991292,0.00001019896,0.000005236566,0.9987866,0.0001830339,0.0006697134,0.0001846589,0.000002904463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09242538,0.000257257,0.9012401,0.0003354429,0.00004512296,0.0002302604,0.0001647239,0.0008884267,0.004413287],"genre_scores_gemma":[0.883306,0.0001128142,0.1143943,0.00005242965,0.00001595404,0.0001515543,0.0001819997,0.000041556,0.001743293],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007248613,"threshold_uncertainty_score":0.01441282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01435257853677909,"score_gpt":0.2268853875200084,"score_spread":0.2125328089832293,"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."}}