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June 12, 2024International Journal of ClimatologyOpen Access

Maximizing daily rainfall prediction accuracy with maximum overlap discrete wavelet transform‐based machine learning models

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Authors

KKKübra KüllahcıIstanbul Technical UniversityAAAbdüsselam AltunkaynakIstanbul Technical University

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Implication

Comparative modeling study demonstrates improved daily rainfall prediction accuracy across three observation stations, suggesting potential for multi-day forecasting.

Key Points

  • Integrating the maximum overlap discrete wavelet transform with machine learning algorithms effectively improves daily rainfall prediction accuracy across multiple stations.
  • Evaluating mean square error and Nash-Sutcliffe coefficient of efficiency shows superior accuracy compared to standard discrete wavelet transform models across all three stations.
  • Analysis of daily rainfall data from three stations enables machine learning algorithms to extend reliable daily rainfall prediction horizons to three days ahead.

Cite This Study

Küllahcı et al. (2024) studied this question.

synapsesocial.com/papers/68e650a7b6db6435875e0f15https://doi.org/10.1002/joc.8530
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