Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Computational intelligence using nailfold videocapillaroscopy for the prediction of carotid intima-media thickness in rheumatoid arthritis: a cohort-based study.

Rheumatology international·2026

Same author

Breast Cancer Biomarker Discovery Using an Enhanced Quantum-Based Avian Navigation Optimizer and Ensemble Learning Model.

IEEE transactions on computational biology and bioinformatics·2026

Same author

Hybrid machine learning approach for predicting compressive strength of sustainable concrete incorporating palm oil fuel ash.

Scientific reports·2026

Same author

Efficient estimation of proton exchange membrane fuel cells parameters using a hybrid swarm intelligent algorithm.

Scientific reports·2026

Same author

Rank charged system search algorithm for optimization and operations research.

Scientific reports·2026

Same author

Machine learning analysis of Iran's wildfire landscape and anthropogenic influences.

Scientific reports·2026

Search research articles

Related Experiment Video

Updated: May 3, 2026

Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

Published on: September 11, 2016

Decision tree approach for soil liquefaction assessment.

Amir H Gandomi¹, Mark M Fridline², David A Roke¹

¹Department of Civil Engineering, The University of Akron, Akron, OH 44325, USA.

Thescientificworldjournal

|February 4, 2014

Summary

Decision tree techniques effectively assess post-earthquake soil liquefaction, outperforming traditional logistic regression models. These methods offer valuable engineering insights for predicting liquefaction potential.

More Related Videos

Integrated Field Lysimetry and Porewater Sampling for Evaluation of Chemical Mobility in Soils and Established Vegetation

Integrated Field Lysimetry and Porewater Sampling for Evaluation of Chemical Mobility in Soils and Established Vegetation

Published on: July 4, 2014

Author Spotlight: Advancing Agricultural Land Ecosystem Research with a Hydraulic Property Analyzer to Assess Soil Health

Author Spotlight: Advancing Agricultural Land Ecosystem Research with a Hydraulic Property Analyzer to Assess Soil Health

Published on: August 9, 2024

Related Experiment Videos

Last Updated: May 3, 2026

Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

Published on: September 11, 2016

Integrated Field Lysimetry and Porewater Sampling for Evaluation of Chemical Mobility in Soils and Established Vegetation

Integrated Field Lysimetry and Porewater Sampling for Evaluation of Chemical Mobility in Soils and Established Vegetation

Published on: July 4, 2014

Author Spotlight: Advancing Agricultural Land Ecosystem Research with a Hydraulic Property Analyzer to Assess Soil Health

Author Spotlight: Advancing Agricultural Land Ecosystem Research with a Hydraulic Property Analyzer to Assess Soil Health

Published on: August 9, 2024

Area of Science:

Geotechnical Engineering
Earthquake Engineering
Data Science

Background:

Soil liquefaction is a significant post-earthquake hazard.
Accurate assessment of liquefaction potential is crucial for infrastructure safety.
Existing models require robust evaluation with advanced techniques.

Purpose of the Study:

To evaluate the performance of decision tree (DT) techniques for post-earthquake soil liquefaction assessment.
To compare the predictive capabilities of DT models against logistic regression (LR).
To interpret the best performing DT models from an engineering perspective.

Main Methods:

Utilized a database of 620 seismic and soil property records.
Applied three distinct decision tree techniques in statistical and engineering contexts.
Developed decision rules using DT algorithms.
Compared DT model results with a logistic regression model.

Main Results:

Decision tree techniques demonstrated high accuracy in predicting soil liquefaction.
DT models outperformed the logistic regression model in performance.
The developed DT models provide interpretable decision rules.

Conclusions:

Decision tree techniques are highly effective for post-earthquake soil liquefaction assessment.
DT models offer a superior alternative to logistic regression for this application.
Engineering-based interpretation of DT models enhances their practical utility in seismic risk analysis.