{"id":"W7104267222","doi":"10.23977/acss.2025.090317","title":"Power Load Forecasting Method Combining Informer Model and ACO Optimization Algorithm","year":2025,"lang":"","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hyperparameter; Ant colony optimization algorithms; Scheduling (production processes); Stability (learning theory); Process (computing); Hyperparameter optimization; Electric power system; Power (physics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001063794,0.0005048115,0.0008001622,0.0003299006,0.0002435624,0.0004223488,0.000190628,0.0002578195,0.000007049348],"category_scores_gemma":[0.0000317652,0.0005189991,0.00007029311,0.0004957117,0.00006767771,0.001179646,0.00024014,0.0003939046,8.349292e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001095145,"about_ca_system_score_gemma":0.00007518274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004521625,"about_ca_topic_score_gemma":0.000007397332,"domain_scores_codex":[0.9972984,0.0001304318,0.00110933,0.0005808062,0.0002739578,0.0006070934],"domain_scores_gemma":[0.9986429,0.0006100026,0.0002290365,0.0002288207,0.0001537335,0.0001355165],"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":[0.000009746854,0.0000150304,0.0003073718,0.0005475931,0.00006183123,0.000008869671,0.001221847,0.7593809,0.00002384969,0.001364129,0.00002025396,0.2370386],"study_design_scores_gemma":[0.00104089,0.0001045628,0.00001135838,0.003536472,0.00003180035,0.00004657263,0.000216046,0.992357,0.00004426191,0.000553651,0.001561328,0.000496101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002741088,0.06537011,0.9226875,0.00001915543,0.002437348,0.0003377105,0.00001563537,0.00008445603,0.006306963],"genre_scores_gemma":[0.6168118,0.004595273,0.3779924,0.0001222032,0.0002092347,0.00004366686,0.00001108183,0.00005421771,0.0001601439],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6140707,"threshold_uncertainty_score":0.9997262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01499022927429781,"score_gpt":0.2607280226944226,"score_spread":0.2457377934201248,"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."}}