Dynamic ensemble-based machine learning models for predicting pest populations

HIGHLIGHTS

• What: The aim of this study is to utilize a timedependent weighting scheme to ensemble forecasts obtained from machine_learning models, such as ANN, SVR, kNN, and RF, using information available on exogenous weather factors for the prediction of pest populations. This study provides a detailed overview of an ensemble model with a timedependent weighting scheme and introduces a time-varying frontiersin.org 10.3389/fams.2024.1435517
• Who: Ankit Kumar Singh from the University of South Africa, South Africa have published the research: Dynamic ensemble-based machine learning models for predicting pest populations, in the . . .
  

   

  

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