Comparative Analysis of LSTM and Random Forest Algorithms for Streamflow Prediction: A Case Study of Diverse River Basins in the United States Article

Shanko, Alemayehu Dula, Melesse, Assefa. (2026). Comparative Analysis of LSTM and Random Forest Algorithms for Streamflow Prediction: A Case Study of Diverse River Basins in the United States . WATER, 18(14), 10.3390/w18141768

cited authors

  • Shanko, Alemayehu Dula; Melesse, Assefa

authors

publication date

  • July 22, 2026

published in

keywords

  • ACCURACY
  • DATA SET
  • Environmental Sciences
  • Environmental Sciences & Ecology
  • LSTM
  • Life Sciences & Biomedicine
  • NEURAL-NETWORK
  • Physical Sciences
  • Science & Technology
  • Water Resources
  • cluster analysis
  • machine learning
  • random forest
  • streamflow prediction

Digital Object Identifier (DOI)

publisher

  • MDPI

volume

  • 18

issue

  • 14