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- W238089792 abstract "Reinforced lightweight soil (RLS) consists of dredged soil taken from construction site of Busan New Port, cement, air foam and waste fishing net. Several series of laboratory tests were performed to investigate the unconfined compressive strength of RLS on various mixing conditions. The unconfined compressive strength as well as stress-strain behavior of lightweight soils strongly depends on mixing conditions including cement content, initial water content, air content and content of waste fishing net. The more the cement content that is added to the mixture, the greater the its unconfined compressive strength. However, the more the initial water content or the more air foam content, the less the its unconfined compressive strength. Therefore it may be difficult to estimate the unconfined compressive strength of lightweight soil at a given mixing condition. In this study, artificial neural network model, which was based on experimental test results performed on various mixing conditions, was applied to predict the unconfined compressive strength. It was found that the unconfined compressive strength of RLS at a given mixing condition could be reasonably estimated using proposed neural network model. In addition, sensitivity analysis was also conducted to evaluate the effect of mixing conditions on the compressive strength." @default.
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- W238089792 date "2007-01-01" @default.
- W238089792 modified "2023-09-26" @default.
- W238089792 title "Prediction of Compressive Strength of Reinforced Lightweight Soil using Artificial Neural Network" @default.
- W238089792 hasPublicationYear "2007" @default.
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