{"id":"W2147819847","doi":"10.1109/ccece.1996.548088","title":"Chaotic simulated annealing in multilayer feedforward networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Attractor; Chaotic; Statistical physics; Simulated annealing; Parametric statistics; Gaussian; Feedforward neural network; Perturbation (astronomy); Feed forward; Computer science; Maxima and minima; Artificial neural network; Mathematics; Applied mathematics; Algorithm; Mathematical analysis; Physics; Artificial intelligence; Statistics","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":[0.0005783455,0.0002965644,0.0004499987,0.000217036,0.0002875827,0.0003413775,0.0004203696,0.0005492349,0.0007227696],"category_scores_gemma":[0.001697283,0.0003027716,0.000440592,0.0002095516,0.0005572957,0.0004789193,0.0005207533,0.0003957932,0.0001141265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006333689,"about_ca_system_score_gemma":0.0003248215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001771946,"about_ca_topic_score_gemma":0.001599972,"domain_scores_codex":[0.999767,0.00008925568,0.0000140112,0.00003204804,0.00007532829,0.00002227176],"domain_scores_gemma":[0.9997252,0.0001583865,0.00003554252,0.00003155919,0.0000375756,0.00001183971],"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":[0.00004597675,0.00001719081,0.0003962693,0.00003578621,0.00002895418,0.00004491273,0.00005611431,0.9665294,0.007366172,0.006437267,0.0001328705,0.01890903],"study_design_scores_gemma":[0.000005950667,0.0000171907,0.00008745409,0.000003462642,0.000003915516,0.000008868311,0.00000249143,0.9963351,0.001572674,0.001611456,0.0003480611,0.000003283564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1136213,0.0004354627,0.8815919,0.0001382114,0.00005180846,0.00005327573,0.00001872519,0.0004557891,0.003633538],"genre_scores_gemma":[0.8172093,0.0002211002,0.1801088,0.00004690122,0.0000179352,0.0001363981,0.00002843072,0.00005301199,0.002178072],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001771946,"threshold_uncertainty_score":0.004595459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02582512529038882,"score_gpt":0.2321085411621003,"score_spread":0.2062834158717114,"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."}}