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Title: Surface settlement modelling using neural network 2
Authors: Khoo, Wei Yang
Keywords: Engineering::Civil engineering::Geotechnical
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Khoo, W. Y. (2021). Surface settlement modelling using neural network 2. Final Year Project (FYP), Nanyang Technological University, Singapore.
Abstract: With an ever-increasing population and scare land, tunnelling underground has emerged as a feasible alternative for providing public works while optimising space use. Ground displacements generated by tunnelling construction is very critical since existing infrastructure and high-rise structures in the urban environment can be very sensitive to any ground movements. The traditional approaches for predicting displacement are focused on empirical studies, which have limitations and does not often provide an accurate estimate due to the complexity and unknown influences. This report will study the use of Artificial Neural Network (ANN) to create a model, capable of predicting settlement. Different analyses will be carried out to obtain the important input parameters and iterations will be done to ensure the accuracy and reliability of the model. With a good model developed, it can be used for future studies and also be tested in situations where the prediction of settlement is required.
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:CEE Student Reports (FYP/IA/PA/PI)

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