AN APPLICATION OF MACHINE LEARNING FOR PREDICTING AIRBORNE CHLORIDE IN COASTAL AREAS

In this study, a machine learning approach using the Isolation Forest, one of the anomaly detection machine learning algorithms, was proposed to exclude anomalous values from the training data. In addition, the influences of the modified training data on the prediction of airborne chloride were inve...

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Veröffentlicht in:	Journal of Structural and Construction Engineering (Transactions of AIJ) 2024/08/01, Vol.89(822), pp.818-829
Hauptverfasser:	SAKIHARA, Kohei, TAKI, Yuta, NAKAMURA, Fuminori, UKEMASU, Kei
Format:	Artikel
Sprache:	jpn
Schlagworte:	Airborne Chloride Algorithms Anomalies Artificial Intelligence Chloride Attack Chlorides Coastal zone Durability Machine Learning Predictions Random Forest Wave height
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