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Milad Mohammadi1, Mohammad Emami Niri2, Abbas Bahroudi1

  • 1School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran.

Scientific reports
|August 21, 2025
PubMed
まとめ

この研究では,マルチ解像度グラフベースのクラスタリング (MRGC) と電気ゾーン指標 (EZI) の方法を統合して,複雑な炭酸水槽における形成抵抗性因子 (FRF) の予測を強化します. この新しいアプローチにより,岩石の分類の精度と貯水池の特徴が著しく改善されます.

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