Iceberg-seabed interaction evaluation in clay seabed using tree-based machine learning algorithms-Reference-Cited by-同舟云学术

Iceberg-seabed interaction evaluation in clay seabed using tree-based machine learning algorithms

Published:2022-12 Issue:4 Volume:2 Page:100075
ISSN:2667-1433
Container-title:Journal of Pipeline Science and Engineering
language:en
Short-container-title:Journal of Pipeline Science and Engineering

Author:

Azimi Hamed,Shiri Hodjat^ORCID,Mahdianpari Masoud

Funder

Research and Development Corporation of Newfoundland and Labrador

Memorial University of Newfoundland

Natural Sciences and Engineering Research Council of Canada

Publisher

Elsevier BV

Subject

Safety, Risk, Reliability and Quality,Mechanical Engineering,Energy (miscellaneous),Fluid Flow and Transfer Processes

Reference23 articles.

1. Multi-objective evolutionary optimization algorithms for machine learning: a recent survey;Alexandropoulos,2019

2. Dimensionless groups of parameters governing the ice-seabed interaction process;Azimi;J. Offshore Mech. Arct. Eng.,2020

3. Evaluation of ice-seabed interaction mechanism in sand by using self-adaptive evolutionary extreme learning machine;Azimi;Ocean Eng.,2021

4. A non-tuned machine learning method to simulate ice-seabed interaction process in clay;Azimi;J. Pipeline Sci. Eng.,2021

5. Ice-seabed interaction modeling in clay by using evolutionary design of generalized group method of data handling;Azimi;Cold Reg. Sci. Technol.,2021

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