{"id":"W2786850658","doi":"10.1109/ssci.2017.8280981","title":"A parallel firefly meta-heuristics algorithm for financial option pricing","year":2017,"lang":"en","type":"article","venue":"","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Firefly algorithm; Speedup; Firefly protocol; Heuristics; Computer science; Computation; Heuristic; Parallel algorithm; Parallel computing; Mathematical optimization; Algorithm; Mathematics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007087698,0.0006056582,0.0007306496,0.0005884705,0.0005062256,0.000624817,0.001197603,0.0009426842,0.00233174],"category_scores_gemma":[0.001187162,0.0003977032,0.0007727786,0.000550011,0.0004080299,0.0006724061,0.0004944673,0.0008680393,0.0005337374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008526979,"about_ca_system_score_gemma":0.001515465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004203599,"about_ca_topic_score_gemma":0.003894765,"domain_scores_codex":[0.9997233,0.00007139951,0.0000117036,0.00005021614,0.00009435447,0.00004905419],"domain_scores_gemma":[0.9997186,0.0001213685,0.00003097707,0.00003692998,0.0000640553,0.00002812578],"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":[0.0001251938,0.0001194919,0.0006707591,0.00008447151,0.00007497805,0.00008295073,0.00005566356,0.8776741,0.005916632,0.01311533,0.002695899,0.09938454],"study_design_scores_gemma":[0.00002888818,0.00002131607,0.00005636388,0.000003686543,0.000007827279,0.00002018523,0.000004313344,0.995937,0.0008076491,0.002083502,0.001024622,0.000004664833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01584585,0.0002613542,0.9786206,0.0001958332,0.00008683635,0.00009121824,0.00004701741,0.0007019528,0.004149236],"genre_scores_gemma":[0.2090355,0.0002433836,0.7866234,0.0001673886,0.00004940853,0.0002201713,0.000122885,0.0001640371,0.003373877],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004203599,"threshold_uncertainty_score":0.00835824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08249262300210236,"score_gpt":0.2762948239804019,"score_spread":0.1938022009782995,"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."}}