{"id":"W2790325559","doi":"10.1002/cjce.23148","title":"An improved economic‐based nonlinear model predictive control strategy for the crude oil distillation process","year":2018,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Model predictive control; Distillation; Profitability index; Weighting; Process (computing); Nonlinear system; Computer science; Process control; Control theory (sociology); Mathematical optimization; Control (management); Mathematics; Artificial intelligence; Chemistry; Economics","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":[0.0007698844,0.0007537313,0.0007960522,0.0003997961,0.0004695674,0.0008174891,0.0009954078,0.0007333694,0.0009023989],"category_scores_gemma":[0.0009011565,0.0003286457,0.0004413854,0.0003966332,0.0005348511,0.0005143937,0.0007431694,0.0006448301,0.0001512033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007568276,"about_ca_system_score_gemma":0.001138187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01224645,"about_ca_topic_score_gemma":0.008040874,"domain_scores_codex":[0.9996948,0.00007090708,0.00001662269,0.00005936923,0.0001206667,0.00003758721],"domain_scores_gemma":[0.9997339,0.00008614134,0.00005072181,0.00001587542,0.0001004102,0.00001284754],"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":[0.00005208593,0.00003194305,0.0002145123,0.00005469287,0.00001932077,0.00005870236,0.00002529092,0.9750462,0.003554924,0.002247821,0.0002659266,0.01842854],"study_design_scores_gemma":[0.000004555404,0.0000136997,0.0000366196,9.248255e-7,0.000003081605,0.00000239115,0.000001022974,0.9994612,0.0002954932,0.0001110116,0.00006833122,0.000001607658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07725239,0.0004900217,0.9130082,0.0003743017,0.00008004101,0.00008576729,0.00003846923,0.0002743716,0.008396535],"genre_scores_gemma":[0.9744655,0.0001403862,0.02343018,0.00004646664,0.00002150228,0.00007481952,0.00002909625,0.00001297182,0.001779154],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01224645,"threshold_uncertainty_score":0.02435035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007023016335816068,"score_gpt":0.2129289234771212,"score_spread":0.2059059071413051,"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."}}