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Optimising Site Investigations Using Monte Carlo Analysis and Genetic Algorithms,n the foundation being larger and more costly than needed. This paper outlines research undertaken to develop such guidance, focusing on the design of pile foundations in variable ground using the probabilistic techniques of random field theory, Monte Carlo simulation and genetic algorithms (GAs). T

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Application of Machine Learning Methods in Estimating Soil Parameters from Dynamic Penetration Testigation, the soil properties such as the shear strength, stiffness, strain rate dependency, and profile non-uniformity may be inferred from the dynamic penetration information by solving a complex inverse analysis problem. In this study, ten alternative machine learning techniques are employed to ex

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Geotechnical Lessons Learnt—Building and Transport Infrastructure Projects

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https://doi.org/10.1007/978-1-4612-3816-4n concept for the development of the design codes, standards and guidelines. From personal experience and observations, as an Australian geotechnical practitioner, a few examples of the application of ASD and LSD methods in small- and large-size projects are presented. Examples include critical desi

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State Subsidies in the Global Economyn the foundation being larger and more costly than needed. This paper outlines research undertaken to develop such guidance, focusing on the design of pile foundations in variable ground using the probabilistic techniques of random field theory, Monte Carlo simulation and genetic algorithms (GAs). T

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