{"id":"W4247716355","doi":"10.5383/ijtee.14.02.003","title":"Prediction of Hourly Solar Radiation in Amman-Jordan by Using Artificial Neural Networks","year":2018,"lang":"en","type":"article","venue":"International Journal of Thermal and Environmental Engineering","topic":"Solar Radiation and Photovoltaics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nonlinear autoregressive exogenous model; Artificial neural network; Feed forward; Autoregressive model; Feedforward neural network; MATLAB; Computer science; Environmental science; Meteorology; Artificial intelligence; Engineering; Mathematics; Statistics; Control engineering; Geography","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":[0.0003459816,0.0003915788,0.000298071,0.0004017504,0.0001979302,0.0004611982,0.0003116938,0.0003128776,0.0003995807],"category_scores_gemma":[0.0006908878,0.0001517493,0.0003260492,0.0005898168,0.00008083749,0.0004222093,0.0001757722,0.0003356319,0.0001541613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003312114,"about_ca_system_score_gemma":0.0003708376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008514829,"about_ca_topic_score_gemma":0.01157283,"domain_scores_codex":[0.9998658,0.00003618826,0.00001416359,0.00002834406,0.00004084948,0.00001456472],"domain_scores_gemma":[0.9998198,0.0000719926,0.00002781938,0.0000099365,0.00006293359,0.000007562391],"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":[0.00006859966,0.00008506005,0.02980544,0.00008044518,0.00007826322,0.0001734194,0.0000857065,0.9233086,0.002537792,0.0002989209,0.0007902855,0.04268752],"study_design_scores_gemma":[0.000004699441,0.00001994524,0.01049013,0.000007758317,0.000008316018,0.00001174948,0.00004734875,0.9879912,0.000844193,0.0001865099,0.0003812626,0.000006813406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9625805,0.0006170436,0.03186911,0.0002154556,0.0000512744,0.00002500109,0.0004473162,0.0002923633,0.003901865],"genre_scores_gemma":[0.9917691,0.0002669285,0.006525524,0.00001402712,0.00001046659,0.00001673939,0.000458745,0.000009999092,0.00092834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008514829,"threshold_uncertainty_score":0.01693052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00973722624376741,"score_gpt":0.1949304053211832,"score_spread":0.1851931790774158,"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."}}