How can Artificial Intelligence be used in Geotechnical Engineering?
Here, because water tanks are more vulnerable structures and plus the tank is sometime overfilled and sometime empty, the pressure inside is so varying, It needs more safety precautions and as we all know working stress method assumes more safety factor than limit state design, which is an economicaRead more
Here, because water tanks are more vulnerable structures and plus the tank is sometime overfilled and sometime empty, the pressure inside is so varying,
It needs more safety precautions and as we all know working stress method assumes more safety factor than limit state design, which is an economical design, we prefer to use working stress method…
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AdityaBhandakkar
Hi, Geotechnical engineering deals with materials (e.g., soil and rock) that, by their very nature, exhibit varied and behavior due to the physical processes associated with the formation of these materials. Modeling such materials' behavior is complicated and usually beyond the ability of most tradRead more
Hi,
Geotechnical engineering deals with materials (e.g., soil and rock) that, by their very nature, exhibit varied and behavior due to the physical processes associated with the formation of these materials. Modeling such materials’ behavior is complicated and usually beyond the ability of most traditional forms of physically-based engineering methods. Artificial intelligence (AI) is becoming more popular and particularly amenable to modeling most geotechnical engineering materials’ complex behavior because it has demonstrated superior predictive ability compared to traditional methods. Over the last decade, AI has been applied successfully to virtually every problem in geotechnical engineering. However, despite this success, AI techniques are still facing classical opposition due to some inherent reasons such as lack of transparency, knowledge extraction, and model uncertainty, which will discuss in detail in this chapter. Among the available AI, techniques are artificial neural networks (ANNs), genetic programming (GP), evolutionary polynomial regression (EPR), support vector machines, M5 model trees, and K-nearest neighbors (Elshorbagy et al.,2010). This chapter will focus on three AI techniques, including ANNs, GP, and EPR.
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