{"id":"W4390646756","doi":"10.23977/jeis.2023.080609","title":"Modeling and optimal design of heliostat field based on particle swarm optimization algorithm","year":2023,"lang":"en","type":"article","venue":"Journal of Electronics and Information Science","topic":"Solar Thermal and Photovoltaic Systems","field":"Energy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Heliostat; Optics; Particle swarm optimization; Nonimaging optics; Solar energy; Computer science; Algorithm; Physics; Engineering; Electrical engineering","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":[0.0005380035,0.001123335,0.001234188,0.000594765,0.0006029291,0.001480275,0.0009716867,0.001191595,0.002556951],"category_scores_gemma":[0.0008000741,0.000669279,0.001106171,0.0005622741,0.0005812858,0.0008606587,0.0008366654,0.0008235011,0.0003127923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007081038,"about_ca_system_score_gemma":0.001601913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01510669,"about_ca_topic_score_gemma":0.005905957,"domain_scores_codex":[0.9997317,0.00005982995,0.00001541768,0.00006219906,0.00008161119,0.0000492289],"domain_scores_gemma":[0.9997802,0.00009101928,0.00002819044,0.00000968431,0.00007315084,0.0000176714],"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":[0.00001173791,0.000009533709,0.0002637852,0.00003574492,0.0000128717,0.0000282231,0.0000190176,0.992428,0.0004327452,0.001621003,0.0003423908,0.004794898],"study_design_scores_gemma":[0.000005850079,0.000008852322,0.00005573815,0.000003075519,0.000003709851,0.000003003707,0.000007033196,0.9992296,0.00006664661,0.0003837474,0.0002305185,0.000002292629],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0217456,0.0006752204,0.9650173,0.0002764023,0.000101003,0.00009664124,0.00008553101,0.0002412514,0.01176115],"genre_scores_gemma":[0.8544156,0.001195885,0.1330232,0.0001777538,0.00007793331,0.0007595553,0.0003349245,0.00008641656,0.009928748],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01510669,"threshold_uncertainty_score":0.03003752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01715609747025018,"score_gpt":0.2465947835211769,"score_spread":0.2294386860509267,"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."}}