0
  • DE
  • EN
  • FR
  • Base de données et galerie internationale d'ouvrages d'art et du génie civil

Publicité

Nii Attoh-Okine

La bibliographie suivante contient toutes les publications répertoriées dans la base de données qui sont reliées à ce nom en tant qu'auteur, éditeur ou collaborateur.

  1. Balogun, Ibrahim / Attoh-Okine, Nii (2023): Covariate-Shift Generative Adversarial Network and Railway Track Image Analysis. Dans: Journal of Transportation Engineering, Part A: Systems, v. 149, n. 3 (mars 2023).

    https://doi.org/10.1061/jtepbs.teeng-7390

  2. Adarkwa, Offei / Attoh-Okine, Nii / Schumacher, Thomas (2017): Using Tensor Factorization to Predict Network-Level Performance of Bridges. Dans: Journal of Infrastructure Systems, v. 23, n. 3 (septembre 2017).

    https://doi.org/10.1061/(asce)is.1943-555x.0000339

  3. Lasisi, Ahmed / Attoh-Okine, Nii (2021): Hybrid Rail Track Quality Analysis using Nonlinear Dimension Reduction Technique with Machine Learning. Dans: Canadian Journal of Civil Engineering / Revue canadienne de génie civil, v. 48, n. 12 (décembre 2021).

    https://doi.org/10.1139/cjce-2019-0832

  4. Bogdanova, Anna / Attoh-Okine, Nii / Sakurai, Tetsuya (2020): Risk and Advantages of Federated Learning for Health Care Data Collaboration. Dans: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, v. 6, n. 3 (septembre 2020).

    https://doi.org/10.1061/ajrua6.0001078

  5. Lasisi, Ahmed / Attoh-Okine, Nii (2019): Machine Learning Ensembles and Rail Defects Prediction: Multilayer Stacking Methodology. Dans: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, v. 5, n. 4 (décembre 2019).

    https://doi.org/10.1061/ajrua6.0001024

  6. Martey, Emmanuel Nii / Attoh-Okine, Nii (2018): Bivariate Severity Analysis of Train Derailments using Copula-Based Regression Models. Dans: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, v. 4, n. 4 (décembre 2018).

    https://doi.org/10.1061/ajrua6.0000982

  7. Galvan-Nunez, Silvia / Attoh-Okine, Nii (2017): Hybrid Particle Swarm Optimization and K-Means Analysis for Bridge Clustering Based on National Bridge Inventory Data. Dans: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, v. 3, n. 2 (juin 2017).

    https://doi.org/10.1061/ajrua6.0000864

  8. Adarkwa, Offei / Attoh-Okine, Nii (2017): Prediction of Structural Deficiency Ratio of Bridges Based on Multiway Data Factorization. Dans: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, v. 3, n. 2 (juin 2017).

    https://doi.org/10.1061/ajrua6.0000882

  9. Adarkwa, Offei Amanor / Attoh-Okine, Nii (2013): Pavement crack classification based on tensor factorization. Dans: Construction and Building Materials, v. 48 (novembre 2013).

    https://doi.org/10.1016/j.conbuildmat.2013.07.091

  10. Atique, Farzana / Attoh-Okine, Nii (2016): Using copula method for pipe data analysis. Dans: Construction and Building Materials, v. 106 (mars 2016).

    https://doi.org/10.1016/j.conbuildmat.2015.12.027

  11. Zarembski, Allan M. / Einbinder, Daniel / Attoh-Okine, Nii (2016): Using multiple adaptive regression to address the impact of track geometry on development of rail defects. Dans: Construction and Building Materials, v. 127 (novembre 2016).

    https://doi.org/10.1016/j.conbuildmat.2016.10.012

  12. Mills, Leslie Odartey / Attoh-Okine, Nii (2014): Analysis of ground penetrating radar data using hierarchical Markov Chain Monte Carlo simulation. Dans: Canadian Journal of Civil Engineering / Revue canadienne de génie civil, v. 41, n. 1 (janvier 2014).

    https://doi.org/10.1139/cjce-2012-0462

  13. Odum-Ewuakye, Brigitte / Attoh-Okine, Nii (2006): Sealing system selection for jointed concrete pavements – A review. Dans: Construction and Building Materials, v. 20, n. 8 (octobre 2006).

    https://doi.org/10.1016/j.conbuildmat.2005.01.042

  14. Atique, Farzana / Attoh-Okine, Nii (2018): Copula parameter estimation using Bayesian inference for pipe data analysis. Dans: Canadian Journal of Civil Engineering / Revue canadienne de génie civil, v. 45, n. 1 (janvier 2018).

    https://doi.org/10.1139/cjce-2017-0084

Rechercher une publication...

Disponible seulement avec
Mon Structurae

Texte intégral
Structurae coopère avec
International Association for Bridge and Structural Engineering (IABSE)
e-mosty Magazine
e-BrIM Magazine