Better with fewer features: climate dynamics estimation for Van Lake basin using feature selection.

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Tác giả: Ferhat Bozkurt, Önder Çoban, Musa Esit, Sercan Yalçın

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: Germany : Environmental science and pollution research international , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 717112

Even though there exist many research efforts trying to develop forecasting models based on machine learning (ML) or statistical techniques, feature selection is not employed in a large majority of the studies. To fill this gap, this study builds prediction models involving feature selection through one-step ahead estimation of climatological parameters (i.e., temperature and evapotranspiration), considering the aforementioned shortcomings. In addition, the best models are used to make estimations for a long horizon of 30 years. The experimental results performed on three stations located at the Van Lake Closed basin of Turkey showed that the Bayesian Ridge regressor (BRR) often outperforms other regressors. The respective best models involving BRR also enabled us to obtain
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