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 …
Remote sensing for assessing landslides and associated hazards
Multi-platform remote sensing using space-, airborne and ground-based sensors has
become essential tools for landslide assessment and disaster-risk prevention. Over the last …
become essential tools for landslide assessment and disaster-risk prevention. Over the last …
Effectiveness assessment of Keras based deep learning with different robust optimization algorithms for shallow landslide susceptibility mapping at tropical area
This research aims at investigating the capability of Keras's deep learning models with three
robust optimization algorithms (stochastic gradient descent, root mean square propagation …
robust optimization algorithms (stochastic gradient descent, root mean square propagation …
Landslide susceptibility index based on the integration of logistic regression and weights of evidence: A case study in Popayan, Colombia
P Goyes-Peñafiel, A Hernandez-Rojas - Engineering Geology, 2021 - Elsevier
In this paper, we present a suitable integration of discrete and continuous data in a unique
methodology based on systematically collected landslide inventory data. Eleven landslide …
methodology based on systematically collected landslide inventory data. Eleven landslide …
Landslide identification using machine learning techniques: Review, motivation, and future prospects
Abstract The WHO (World Health Organization) study reports that, between 1998-2017, 4.8
million people have been affected by landslides with more than 18000 deaths. The …
million people have been affected by landslides with more than 18000 deaths. The …
An optimized combination prediction model for concrete dam deformation considering quantitative evaluation and hysteresis correction
Certain degree of deformation is natural while dam operates and evolves. Due to the impact
of internal and external environment, dam deformation is highly nonlinear by nature. For …
of internal and external environment, dam deformation is highly nonlinear by nature. For …
Effectiveness of Newmark-based sampling strategy for coseismic landslide susceptibility mapping using deep learning, support vector machine, and logistic …
Non-landslide samples play a crucial role in landslide susceptibility mapping (LSM),
although unsuitable sampling methods may degrade the performance of the prediction …
although unsuitable sampling methods may degrade the performance of the prediction …
A novel whale optimization algorithm optimized XGBoost regression for estimating bearing capacity of concrete piles
This paper presents a hybrid model combining the extreme gradient boosting machine
(XGBoost) and the whale optimization algorithm (WOA) to predict the bearing capacity of …
(XGBoost) and the whale optimization algorithm (WOA) to predict the bearing capacity of …
Image Processing‐Based Pitting Corrosion Detection Using Metaheuristic Optimized Multilevel Image Thresholding and Machine‐Learning Approaches
ND Hoang - Mathematical Problems in Engineering, 2020 - Wiley Online Library
Pitting corrosion can lead to critical failures of infrastructure elements. Therefore, accurate
detection of corroded areas is crucial during the phase of structural health monitoring. This …
detection of corroded areas is crucial during the phase of structural health monitoring. This …
Hybrid machine learning approach for landslide prediction, Uttarakhand, India
P Kainthura, N Sharma - Scientific reports, 2022 - nature.com
Natural disasters always have a damaging effect on our way of life. Landslides cause
serious damage to both human and natural resources around the world. In this paper, the …
serious damage to both human and natural resources around the world. In this paper, the …