Predicting and Improvising the Performance of Rocket Nozzle Throat Using Machine Learning Algorithms
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Vijayalakshmi et al. (2020) uses student ratings related to class planning, presentation, management, and student participation to directly predict instructor performance.
“Vijayalakshmi et al. (2020) uses student ratings related to class planning, presentation, management, and student participation to directly predict instructor performance.”
From Proactive and reactive engagement of artificial intelligence methods for education: a review (2023) · cites this paper as Vijayalakshmi et al. (2020)
Cited by
Sorted by citations
Proactive and reactive engagement of artificial intelligence methods for education: a review
Mallik, S., & Gangopadhyay, A. (2023) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2023.1151391 · Cited by 139 · see citing works
“[246] uses student ratings related to class planning, presentation, management and student participation to directly predict instructor performance.”
Background
- Authors
- Krishna, A. V. N.
- Corresponding author
- Krishna, Addepalli V.N.
- Venue
- Journal of Advanced Research in Dynamical and Control Systems
- Published
- 2020-03-31
- Volume
- 12
- Issue
- SP4
- Pages
- 16-20
- ISSN
- 1943-023X (ISSN-L)
- OpenAlex
- W3021146136
- Cited by
- 1
- References
- 0
- Citations by year
- 2023: 1
- FWCI
- 0.15
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Advanced Research in Dynamical and Control Systems (publishedVersion)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Rocket and propulsion systems research
- Physical Sciences › Engineering › Control and Systems Engineering › Aerospace Engineering and Applications
- Physical Sciences › Engineering › Aerospace Engineering › Turbomachinery Performance and Optimization
- Keywords
- rocket nozzle, nozzle throat, performance prediction, performance improvement, machine learning, rocket propulsion
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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