Application of Artificial Intelligence to Determined Unconfined Compressive Strength of Cement-Stabilized Soil in Vietnam
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Application of Artificial Intelligence to Determined Unconfined Compressive Strength of Cement-Stabilized Soil in Vietnam
Authors
Keywords
-
Journal
Applied Sciences-Basel
Volume 11, Issue 4, Pages 1949
Publisher
MDPI AG
Online
2021-02-24
DOI
10.3390/app11041949
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A Novel Hybrid Soft Computing Model Using Random Forest and Particle Swarm Optimization for Estimation of Undrained Shear Strength of Soil
- (2020) Binh Thai Pham et al. Sustainability
- An Experimental Study on Unconfined Compressive Strength of Soft Soil-Cement Mixtures with or without GGBFS in the Coastal Area of Vietnam
- (2020) Son Bui Truong et al. Advances in Civil Engineering
- Design deep neural network architecture using a genetic algorithm for estimation of pile bearing capacity
- (2020) Tuan Anh Pham et al. PLoS One
- Effect of Lithium-Slag in the Performance of Slag Cement Mortar Based on Least-Squares Support Vector Machine Prediction
- (2019) Jianghu Lu et al. Materials
- An Improved Gradient Boosting Regression Tree Estimation Model for Soil Heavy Metal (Arsenic) Pollution Monitoring Using Hyperspectral Remote Sensing
- (2019) Lifei Wei et al. Applied Sciences-Basel
- Correlation Coefficients
- (2018) Patrick Schober et al. ANESTHESIA AND ANALGESIA
- Full-scale mechanically stabilized earth (MSE) walls under strip footing load
- (2018) Hamzeh Ahmadi et al. GEOTEXTILES AND GEOMEMBRANES
- Influences of Specimen Geometry and Loading Rate on Compressive Strength of Unstabilized Compacted Earth Block
- (2018) Guan-qi Lan et al. Advances in Materials Science and Engineering
- Effect of water content and density on strength and deformation behavior of clay soils
- (2018) John P. Malizia et al. ENGINEERING GEOLOGY
- Assessment of spatial hybrid methods for predicting soil organic matter using DEM derivatives and soil parameters
- (2018) Panagiotis Tziachris et al. CATENA
- Combining Partial Least Squares and the Gradient-Boosting Method for Soil Property Retrieval Using Visible Near-Infrared Shortwave Infrared Spectra
- (2017) Lanfa Liu et al. Remote Sensing
- Peak Shear Strength of Discrete Fiber-Reinforced Soils Computed by Machine Learning and Metaensemble Methods
- (2016) Jui-Sheng Chou et al. JOURNAL OF COMPUTING IN CIVIL ENGINEERING
- Physical and geotechnical properties of cement-treated clayey soil using silica nanoparticles: An experimental study
- (2016) N. Ghasabkolaei et al. European Physical Journal Plus
- Effect of length-to-diameter ratio on the unconfined compressive strength of cohesive soil specimens
- (2015) Hakan Güneyli et al. Bulletin of Engineering Geology and the Environment
- A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape
- (2015) Kennedy Were et al. ECOLOGICAL INDICATORS
- GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran
- (2015) Seyed Amir Naghibi et al. ENVIRONMENTAL MONITORING AND ASSESSMENT
- Modeling of ground motion rotational components for near-fault and far-fault earthquake according to soil type
- (2014) Lila Kalani Sarokolayi et al. Arabian Journal of Geosciences
- Why Should Ensemble Spread Match the RMSE of the Ensemble Mean?
- (2014) V. Fortin et al. JOURNAL OF HYDROMETEOROLOGY
- Soft ground improvement via vertical drains and vacuum assisted preloading
- (2011) B. Indraratna et al. GEOTEXTILES AND GEOMEMBRANES
- Field Investigations on Performance of T-Shaped Deep Mixed Soil Cement Column–Supported Embankments over Soft Ground
- (2011) Song-Yu Liu et al. JOURNAL OF GEOTECHNICAL AND GEOENVIRONMENTAL ENGINEERING
- Predict soil texture distributions using an artificial neural network model
- (2008) Zhengyong Zhao et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started