Evidence map›Paper›PMID 36825173›Full record

ArticleHeliyon2023

Improving extreme offshore wind speed prediction by using deconvolution.

Oleg Gaidai, Yihan Xing, Rajiv Balakrishna, Jingxiang Xu

RetractedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Dementia death rates prediction.BMC psychiatry · 2023
    Article
  7. Carbon Storage Tanker Lifetime Assessment.Global challenges (Hoboken, NJ) · 2023
    Article
  8. Oil tanker under ice loadings.Scientific reports · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

  • Retraction · 2025-07-15Concerns/Issues about Referencing/Attributions · Investigation by Journal/Publisher · Objections by Author(s) · Unreliable Results and/or Conclusions ·
5 · Who and what money

Authors and funding

4 authors.

Oleg GaidaiShanghai Engineering Research Center of Hadal Science and Technology, College of Engineering Science and Technology, Shanghai Ocean University, China.
Yihan XingUniversity of Stavanger, Norway.
Rajiv BalakrishnaUniversity of Stavanger, Norway.
Jingxiang XuShanghai Engineering Research Center of Hadal Science and Technology, College of Engineering Science and Technology, Shanghai Ocean University, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study proposes an innovative method for predicting extreme values in offshore engineering. This includes and is not limited to environmental loads due to offshore wind and waves and related structural reliability issues. Traditional extreme value predictions are frequently constructed using certain statistical distribution functional classes. The proposed method differs from this as it does not assume any extrapolation-specific functional class and is based on the data set's intrinsic qualities. To demonstrate the method's effectiveness, two wind speed data sets were analysed and the forecast accuracy of the suggested technique has been compared to the Naess-Gaidai extrapolation method. The original batch of data consisted of simulated wind speeds. The second data related to wind speed was recorded at an offshore Norwegian meteorological station.

Indexed as

ConvolutionExtreme wind speed estimationMeasured wind speed dataOffshore windReliability

Identifiers

PMID36825173
PMCPMC9941992

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.