XGBoost algorithm-based prediction of safety assessment for pipelines
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
XGBoost algorithm-based prediction of safety assessment for pipelines
Authors
Keywords
Pipeline welds, Risk assessment, XGBoost model, Machine learning
Journal
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
Volume 197, Issue -, Pages 104655
Publisher
Elsevier BV
Online
2022-03-25
DOI
10.1016/j.ijpvp.2022.104655
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- An Assessment on a Subsea Pipeline Subject to a Diagonal Trawl Impact
- (2021) Farhad Davaripour et al. APPLIED OCEAN RESEARCH
- A Machine Learning Processing Pipeline for Reliable Hand Gesture Classification of FMG Signals with Stochastic Variance
- (2021) Mohammed Asfour et al. SENSORS
- Predicting pipeline burst pressures with machine learning models
- (2021) Hieu Chi Phan et al. INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
- Comparison of different machine learning algorithms for predicting the SAGD production performance
- (2021) Ziteng Huang et al. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
- Large deformation coupled analysis of embedded pipeline – Soil lateral interaction
- (2021) Xiaoyu Dong et al. MARINE STRUCTURES
- Effect of damage progression on the plastic capacity of a subsea pipeline
- (2021) Farhad Davaripour et al. OCEAN ENGINEERING
- An Active Learning Polynomial Chaos Kriging metamodel for reliability assessment of marine structures
- (2021) Aghatise Okoro et al. OCEAN ENGINEERING
- Data-driven operational failure likelihood model for microbiologically influenced corrosion
- (2021) Mohammad Zaid Kamil et al. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
- Evaluation of ice-seabed interaction mechanism in sand by using self-adaptive evolutionary extreme learning machine
- (2021) Hamed Azimi et al. OCEAN ENGINEERING
- Operational subsea pipeline assessment affected by multiple defects of microbiologically influenced corrosion
- (2021) Mohammad Yazdi et al. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
- Offshore system safety and reliability considering microbial influenced multiple failure modes and their interdependencies
- (2021) Sidum Adumene et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Balancing composite motion optimization
- (2020) Thang Le-Duc et al. INFORMATION SCIENCES
- Predictive model for water absorption in sublayers using a Joint Distribution Adaption based XGBoost transfer learning method
- (2020) Wei Liu et al. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
- Review on Computer Aided Weld Defect Detection from Radiography Images
- (2020) Wenhui Hou et al. Applied Sciences-Basel
- Using the XGBoost algorithm to classify neck and leg activity sensor data using on-farm health recordings for locomotor-associated diseases
- (2020) M. Gertz et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- A state of the art review on condition assessment models developed for sewer pipelines
- (2020) Alaa Hawari et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- A new hybrid algorithm model for prediction of internal corrosion rate of multiphase pipeline
- (2020) Shanbi Peng et al. Journal of Natural Gas Science and Engineering
- Subsea Pipelines Leak-Modeling Using Computational Fluid Dynamics Approach
- (2020) Yousef Abdulhafed Yousef et al. Journal of Pipeline Systems Engineering and Practice
- Bayesian Survival Analysis Model for Girth Weld Failure Prediction
- (2019) Qingshan Feng et al. Applied Sciences-Basel
- Novel framework for image attribute annotation with gene selection XGBoost algorithm and relative attribute model
- (2019) Hongbin Zhang et al. APPLIED SOFT COMPUTING
- Developing window behavior models for residential buildings using XGBoost algorithm
- (2019) Hao Mo et al. ENERGY AND BUILDINGS
- Efficient drone hijacking detection using two-step GA-XGBoost
- (2019) Zhiwei Feng et al. JOURNAL OF SYSTEMS ARCHITECTURE
- Data-driven risk assessment on urban pipeline network based on a cluster model
- (2019) Zifeng Wang et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- A novel methodology to update the reliability of the corroding natural gas pipeline by introducing the effects of failure data and corrective maintenance
- (2018) Weichao Yu et al. INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
- Matching pipeline In-line inspection data for corrosion characterization
- (2018) Huan Liu et al. NDT & E INTERNATIONAL
- A review on pipeline corrosion, in-line inspection (ILI), and corrosion growth rate models
- (2017) H.R. Vanaei et al. INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
- Automated detection of welding defects in pipelines from radiographic images DWDI
- (2017) Neury Boaretto et al. NDT & E INTERNATIONAL
- A review on welding of high strength oil and gas pipeline steels
- (2017) Satish Kumar Sharma et al. Journal of Natural Gas Science and Engineering
- Artificial neural network models for predicting condition of offshore oil and gas pipelines
- (2014) Mohammed S. El-Abbasy et al. AUTOMATION IN CONSTRUCTION
- Multiclass defect detection and classification in weld radiographic images using geometric and texture features
- (2010) Ioannis Valavanis et al. EXPERT SYSTEMS WITH APPLICATIONS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search