Land Reclamation Management Utilizing Artificial Intelligence for Estimating Soil Properties
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Abstract
In use of clayey soils to effectively use clayey soils for land reclamation from the viewpoint of sustainable development, the stability against slip and future consolidation settlement should be examined during and after reclamation. For these purposes, a practical reclamation management system has been developed integrating an artificial intelligence (AI) estimation of soil properties, deposition shape analysis, and consolidation settlement analysis for clayey soils dumped from a hopper barge for reclamation. The AI technique for estimating of soil properties is characterized by use of a convolutional neural network (CNN) based on information such as soil source, wet density, and photographed image obtained before reclamation works. In this study, the validity of each analysis model in the practical system has been verified on an actual reclamation project by comparing analysis results with the measured data such as deposition shape of dumped soils on the seabed, soil properties in the reclaimed ground and monitored consolidation settlement after reclamation and soil improvement works.
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Copyright © 2019 Association of Geotechnical Societies in Southeast Asia (AGSSEA) - Southeast Asian Geotechnical Society (SEAGS).
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