Results of training and prediction of death population for SSA-XGBoost model.

<p>Results of training and prediction of death population for SSA-XGBoost model.</p>

Furkejuvvon:

Bibliográfalaš dieđut
Váldodahkki:	Jin Wang (29560) (author)
Eará dahkkit:	Shihan Ma (9362796) (author), Qing Lv (63057) (author), Qiang Li (8118) (author)
Almmustuhtton:	2025
Fáttát:	Ecology Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified sparrow search algorithm population forecasts due population dynamic monitoring mobile phone signals high population density different metaheuristic algorithms research focuses primarily mean squared error reliable predictive model div >< p 2 </ sup improve forecast accuracy better prediction performance xgboost model demonstrates proposed predictive model demographic data forecast effectively forecast research compared higher error demographic data better r combination model base model verified based various gradient validation show time characteristics reasonable parameters predicted data national regions machine learning learning models hebei province following year economic planning comparative experiments boosting machine
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