How statistical modeling and machine learning could help in the calibration of numerical simulation and fluid mechanics models? Application to the calibration of models reproducing the vibratory behavior of an overhead line conductor

No abstract is available for this paper.

• Publication year

  2022

• Venue

  Array

• Publication date

  2022-05-01

• Fields of study

  Physics, Computer Science, Engineering

• Identifiers
  DOI 10.1016/j.array.2022.100187
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Eye tracking algorithms, techniques, tools, and applications with an emphasis on machine learning and Internet of Things technologies

  2021cited by this paper
• VIV modelled using simplified cable dynamics coupled to sub-critical cylinder flow simulations in a moving reference frame

  2021cited by this paper
• Proof of concept: Calibration of an overhead line conductors’ movements simulation model using Ensemble-based machine learning model

  2021cited by this paper
• OC-SMART: A machine learning based data analysis platform for satellite ocean color sensors

  2021cited by this paper
• Machine learning discriminates a movement disorder in a zebrafish model of Parkinson's disease

  2020cited by this paper
• An efficient XGBoost–DNN-based classification model for network intrusion detection system

  2020cited by this paper
• Achieving accurate estimates of fetal gestational age and personalised predictions of fetal growth based on data from an international prospective cohort study: a population-based machine learning study

  2020cited by this paper
• Novel Development of Predictive Feature Fingerprints to Identify Chemistry-Based Features for the Effective Drug Design of SARS-CoV-2 Target Antagonists and Inhibitors Using Machine Learning

  2020cited by this paper
• OceanSODA-ETHZ: a global gridded data set of the surface ocean carbonate system for seasonal to decadal studies of ocean acidification

  2020cited by this paper
• Predicting Missing Values in Medical Data Via XGBoost Regression

  2020cited by this paper
• Supplementary material to "A comparative assessment of the uncertainties of global surface­-ocean CO2 estimates using a machine learning ensemble (CSIR-ML6 version 2019a) – have we hit the wall?"

  2019cited by this paper
• A machine learning approach to estimate surface ocean pCO2 from satellite measurements

  2019cited by this paper
• How Effective Was the UK Carbon Tax?—A Machine Learning Approach to Policy Evaluation

  2019cited by this paper
• Augmenting Pre-Analysis Plans with Machine Learning

  2019cited by this paper
• Predicting Motor Insurance Claims Using Telematics Data—XGBoost versus Logistic Regression

  2019cited by this paper
• Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

  2019cited by this paper
• Evaluating Optimization Strategies for Engine Simulations Using Machine Learning Emulators

  2018cited by this paper
• An open experimental database for exploring inorganic materials

  2018cited by this paper
• A hybrid algorithm of particle swarm optimization, metropolis criterion and RTS smoother for path planning of UAVs

  2018cited by this paper
• Thermal-Sensor-Based Occupancy Detection for Smart Buildings Using Machine-Learning Methods

  2018cited by this paper
• Making Machine-Learning Applications for Time-Series Sensor Data Graphical and Interactive

  2017cited by this paper
• HOME: a histogram based machine learning approach for effective identification of differentially methylated regions

  2017cited by this paper
• Revolt: Collaborative Crowdsourcing for Labeling Machine Learning Datasets

  2017cited by this paper
• Data Mining and Analytics in the Process Industry: The Role of Machine Learning

  2017cited by this paper
• Recognition of human activity using Internet of Things in a non-controlled environment

  2016cited by this paper
• Approval Voting and Incentives in Crowdsourcing

  2015cited by this paper
• FUBAR: A Fast, Unconstrained Bayesian AppRoximation for Inferring Selection

  2014cited by this paper
• Local search algorithms

  2008cited by this paper
• Computation of vortex-induced vibrations of long structures using a wake oscillator model: Comparison with DNS and experiments

  2007cited by this paper
• A New Perspective on V3 Phenotype Prediction

  2003cited by this paper
• Deep‐Sea Benthic Foraminiferal Assemblage Response to a Surface Ocean Productivity Gradient: A Test

  1991cited by this paper
• The ideal teaching machine

  1986cited by this paper

• Pathways to identify and reduce uncertainties in agricultural climate impact assessments

  2024cites this paper