An optimized XGBoost-based machine learning method for predicting wave run-up on a sloping beach
- DOI
- 10.1016/j.mex.2023.102119
- Published
- 2023
- Container
- MethodsX
- Publisher
- Elsevier BV
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1016/j.mex.2023.102119,
title = {An optimized XGBoost-based machine learning method for predicting wave run-up on a sloping beach},
author = {Dede Tarwidi and Sri Redjeki Pudjaprasetya and Didit Adytia and Mochamad Apri},
year = {2023},
journal = {MethodsX},
doi = {10.1016/j.mex.2023.102119},
url = {https://doi.org/10.1016/j.mex.2023.102119}
}RIS
TY - JOUR TI - An optimized XGBoost-based machine learning method for predicting wave run-up on a sloping beach AU - Dede Tarwidi AU - Sri Redjeki Pudjaprasetya AU - Didit Adytia AU - Mochamad Apri PY - 2023 JO - MethodsX DO - 10.1016/j.mex.2023.102119 UR - https://doi.org/10.1016/j.mex.2023.102119 ER -
APA
Tarwidi, D., Pudjaprasetya, S. R., Adytia, D., & Apri, M. (2023). An optimized XGBoost-based machine learning method for predicting wave run-up on a sloping beach. MethodsX. https://doi.org/10.1016/j.mex.2023.102119
Source records
- crossref · retrieved 2026-09-26T02:41:46.546Z