Skip to main content
Theodore Ray
Planning and development surveyor
Asked a question 2 years ago

How can Artificial Intelligence be used in Geotechnical Engineering?

How can Artificial Intelligence be used in Geotechnical Engineering?

Where am I?

In TheConstructor you can ask and answer questions and share your experience with others!

Henry Newman
Water resource engineer

Artificial intelligence in geotechnical engineering:

Hi Ray,

Basically the artificial intelligence systems are used to protect many aspects of geotechnical Engineering

We can use artificial intelligence in that field where uncertainty exist such as Rock and soil properties

We can definitely use artificial intelligence in the constitutive relationships and prediction of settlement

For finding out the bearing capacity of given soil sample and liquefaction we can definitely use artificial intelligence system.

With the help of artificial intelligence  we can investigate  the long term performance of payments very effectively without introducing any manual error in it.

We can definitely use artificial intelligence in the field of rockfall as well as slope stability evaluations.

I hope so you found my answer helpful to you.

Thank You.


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.