Abstract
A new study on artificial intelligence is now available. According to news originating from the Korea Institute of Civil Engineering and Building Technology by NewsRx correspondents, research stated, “As large cities are continually being developed around coastal areas, structural damage due to the consolidation settlement of soft ground is becoming more of a problem.” Financial supporters for this research include Korea Institute of Civil Engineering And Building Technology. The news correspondents obtained a quote from the research from Korea Institute of Civil Engineering and Building Technology: “Estimating consolidation settlement requires calculating an accurate compressive index through consolidation tests. However, these tests are time-consuming, and there is a risk of the test results becoming compromised while preparing and testing the specimens. Therefore, predicting the compression index based on the results of relatively simple physical property tests enables more reliable and accurate predictions of consolidation settlement by calculating the compression index at multiple points. In this context, this study collected geotechnical data from the soft ground of Korea’s south coast. The collected data were used to construct a dataset for developing a compression index prediction model, and significant influencing factors were identified through Pearson correlation analysis. Simple and multiple linear regression analysis was performed using these factors to derive regression equations, and compression index prediction models were developed by applying machine learning algorithms.”
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