Expression of concern: Machine learning models for biogas potential in sustainable aviation: XG boost, random forest and ridge regression

The publisher of Aircraft Engineering and Aerospace Technology is issuing an Expression of Concern for the following article Alkharashi, A., Al Mazroa, A., M. Alashjaee, A., V., S., M., D.B., S., S. and S., V. (2025), “Machine learning models for biogas potential in sustainable aviation: XG Boost, random forest and ridge regression,” Aircraft Engineering and Aerospace Technology, Vol. ahead-of-print No. ahead-of-print. Link to the cited article., which was submitted to the guest-edited special issue “AI Applications in High-Speed Aerospace Propulsion Systems,” to inform readers that concerns have been raised regarding its authorship. This special issue has subsequently been canceled. An investigation by the publisher found a number of articles with multiple concerns, including but not limited to lack of suitability for the scope of the journal and special issue, evidence of third-party involvement, and the inclusion of irrelevant citations. The following citations have been identified as anomalous and inappropriate; the authors were unable to provide sufficient justification for their presence in the article:Varuthaiya, M., Palanisamy, C., Sivakumar, V. and Pushpanathan, G. (2022), “Concrete with sisal fibered geopolymer: a behavioral study”, Journal of Ceramic Processing Research, Vol. 23 No. 6, pp. 912-919.Verapathran, M., Vivek, S., Arunkumar, G.E. and Dhavashankaran, D. (2023), “Flexural behaviour of HPC beams with steel slag aggregate”, Journal of Ceramic Processing Research, Vol. 24 No. 1, pp. 89-97.An investigation is ongoing and is currently unresolved. Further information will be provided by Aircraft Engineering and Aerospace Technology as it becomes available. The publisher of the journal sincerely apologizes to the readers of this article.

Publication Details

Journal
Aircraft Engineering and Aerospace Technology
Published
2026-02-23
DOI
https://doi.org/10.1108/aeat-02-2026-0064
Primary Topic
Internet of Things and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Expression of concern: Machine learning models for biogas potential in sustainable aviation: XG boost, random forest and ridge regression

Aircraft Engineering and Aerospace Technology
Internet of Things and AI
article

Expression of concern: Machine learning models for biogas potential in sustainable aviation: XG boost, random forest and ridge regression

article en

Abstract

The publisher of Aircraft Engineering and Aerospace Technology is issuing an Expression of Concern for the following article Alkharashi, A., Al Mazroa, A., M. Alashjaee, A., V., S., M., D.B., S., S. and S., V. (2025), “Machine learning models for biogas potential in sustainable aviation: XG Boost, random forest and ridge regression,” Aircraft Engineering and Aerospace Technology, Vol. ahead-of-print No. ahead-of-print. Link to the cited article., which was submitted to the guest-edited special issue “AI Applications in High-Speed Aerospace Propulsion Systems,” to inform readers that concerns have been raised regarding its authorship. This special issue has subsequently been canceled. An investigation by the publisher found a number of articles with multiple concerns, including but not limited to lack of suitability for the scope of the journal and special issue, evidence of third-party involvement, and the inclusion of irrelevant citations. The following citations have been identified as anomalous and inappropriate; the authors were unable to provide sufficient justification for their presence in the article:Varuthaiya, M., Palanisamy, C., Sivakumar, V. and Pushpanathan, G. (2022), “Concrete with sisal fibered geopolymer: a behavioral study”, Journal of Ceramic Processing Research, Vol. 23 No. 6, pp. 912-919.Verapathran, M., Vivek, S., Arunkumar, G.E. and Dhavashankaran, D. (2023), “Flexural behaviour of HPC beams with steel slag aggregate”, Journal of Ceramic Processing Research, Vol. 24 No. 1, pp. 89-97.An investigation is ongoing and is currently unresolved. Further information will be provided by Aircraft Engineering and Aerospace Technology as it becomes available. The publisher of the journal sincerely apologizes to the readers of this article.

Aircraft Engineering and Aerospace TechnologyVol. 98(4)
Responsible consumption and production
Openalex Percentile: Top 62%
Internet of Things and AI
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