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Application of artificial intelligence in geotechnical engineering: A state-of-the-art review
Geotechnical engineering deals with soils and rocks and their use in engineering
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …
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The present research was conducted around Choke Mountain, East Gojjam, Northwestern
Ethiopia. This study aimed to apply and validate analytical hierarchy process (AHP) and …
Ethiopia. This study aimed to apply and validate analytical hierarchy process (AHP) and …
Comparison of tree-based machine learning algorithms for predicting liquefaction potential using canonical correlation forest, rotation forest, and random forest based …
This research investigates and compares the performance of three tree-based Machine
Learning (ML) methods, Canonical Correlation Forest (CCF), Rotation Forest (RotFor), and …
Learning (ML) methods, Canonical Correlation Forest (CCF), Rotation Forest (RotFor), and …
Evaluation of soil liquefaction using AI technology incorporating a coupled ENN/t-SNE model
This paper presents a new evolutionary neural network (ENN) algorithm coupled with the
dimensionality reduction technique 't-distributed stochastic neighbour embedding'(t-SNE) …
dimensionality reduction technique 't-distributed stochastic neighbour embedding'(t-SNE) …
An exploration of the use of machine learning to predict lateral spreading
The recent availability of large amounts of high-quality data from post-disaster field
reconnaissance enables an exploration of the use of machine learning (ML) approaches to …
reconnaissance enables an exploration of the use of machine learning (ML) approaches to …
Why “AI” models for predicting soil liquefaction have been ignored, plus some that shouldn't be
BW Maurer, MD Sanger - Earthquake Spectra, 2023 - journals.sagepub.com
Soil liquefaction remains an important and interesting problem that has attracted the
development of enumerable prediction models. Increasingly, these models are utilizing …
development of enumerable prediction models. Increasingly, these models are utilizing …
An extreme learning machine approach for slope stability evaluation and prediction
This paper presents slope stability evaluation and prediction with the approach of a fast
robust neural network named the extreme learning machine (ELM). The circular failure …
robust neural network named the extreme learning machine (ELM). The circular failure …