Failure risk analysis of pipelines using data-driven machine learning algorithms

Failure mode and effects analysis of RC members based on machine-learning-based SHapley Additive exPlanations (SHAP) approach

(2020) Sujith Mangalathu et al.   ENGINEERING STRUCTURES

Reliability assessments of corroded pipelines based on internal pressure – A review

(2019) Rafael Amaya-Gómez et al.   ENGINEERING FAILURE ANALYSIS

Machine Learning for Modeling Water Demand

(2019) Maria C. Villarin et al.   JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT

On the application of machine learning techniques to derive seismic fragility curves

(2019) Jalal Kiani et al.   COMPUTERS & STRUCTURES

The impact of class imbalance in classification performance metrics based on the binary confusion matrix

(2019) Amalia Luque et al.   PATTERN RECOGNITION

Machine Learning–Based Failure Mode Recognition of Circular Reinforced Concrete Bridge Columns: Comparative Study

(2019) Sujith Mangalathu et al.   JOURNAL OF STRUCTURAL ENGINEERING

Analytical prediction of failure pressure for pipeline with long corrosion defect

(2019) Jie Gao et al.   OCEAN ENGINEERING

A Review of Failure Prediction Models for Oil and Gas Pipelines

(2019) Kimiya Zakikhani et al.   Journal of Pipeline Systems Engineering and Practice

Machine learning algorithms for structural performance classifications and predictions: Application to reinforced masonry shear walls

(2019) Ahmad Siam et al.   Structures

Prediction of pipe failures in water supply networks using logistic regression and support vector classification

(2019) Alicia Robles-Velasco et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

An experimental investigation of the effect of defect shape and orientation on the burst pressure of pressurised pipes

(2018) Sultan Al-Owaisi et al.   ENGINEERING FAILURE ANALYSIS

Classification of failure mode and prediction of shear strength for reinforced concrete beam-column joints using machine learning techniques

(2018) Sujith Mangalathu et al.   ENGINEERING STRUCTURES

Seismic fragility analysis with artificial neural networks: Application to nuclear power plant equipment

(2018) Zhiyi Wang et al.   ENGINEERING STRUCTURES

A machine learning framework for assessing post-earthquake structural safety

(2018) Yu Zhang et al.   STRUCTURAL SAFETY

Pipe failure modelling for water distribution networks using boosted decision trees

(2018) Daniel Winkler et al.   Structure and Infrastructure Engineering

Reliability Analysis of Water Distribution Systems Using Physical Probabilistic Pipe Failure Method

(2018) Ram K. Mazumder et al.   JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT

Statistical models for shear strength of RC beam-column joints using machine-learning techniques

(2014) Jong-Su Jeon et al.   EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS

Surrogate modeling and failure surface visualization for efficient seismic vulnerability assessment of highway bridges

(2013) Jayadipta Ghosh et al.   PROBABILISTIC ENGINEERING MECHANICS

Evaluating Fitness-for-Service of Corroded Metal Pipelines: Structural Reliability Bases

(2013) Naiyu Wang et al.   Journal of Pipeline Systems Engineering and Practice

Towards automatic lithological classification from remote sensing data using support vector machines

(2011) Le Yu et al.   COMPUTERS & GEOSCIENCES

Probability assessment of burst limit state due to internal corrosion

(2011) Sikder Hasan et al.   INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING

Comparing three methods for modeling the uncertainty in knowledge discovery from area-class soil maps

(2010) Feng Qi et al.   COMPUTERS & GEOSCIENCES

Probability distribution of pitting corrosion depth and rate in underground pipelines: A Monte Carlo study

(2009) F. Caleyo et al.   CORROSION SCIENCE

Risk assessment for pipelines with active defects based on artificial intelligence methods

(2009) Calin I. Anghel   INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING

Reliability of pipelines with corrosion defects

(2007) A.P. Teixeira et al.   INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING