The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Neural networks analysis of thermal characteristics on plate-fin heat exchangers with limited experimental data
Overview
Integrity signals
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Cites
Statistics
Verification
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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?
In the citing paper
“A generalized j - and f - factor correlations were recently formulated [89] by using numerical simulation by testing 55 strip-fin cores; the results were in excellent agreement with those of experimental data [40, 86, 90].”
From Compact and microchannel heat exchangers: A comprehensive review of air-side friction factor and heat transfer correlations (2018) · cites this paper as [90]
Citations
Cites
Holman, J. P. (1976) · Cited by 9,157
Neural network analysis of fin-tube refrigerating heat exchanger with limited experimental data
Pacheco-Vega, A., Sen, M., Yang, K. T., & McClain, R. L. (2001) · International Journal of Heat and Mass Transfer · doi:10.1016/s0017-9310(00)00139-3 · Cited by 230
Confidence interval prediction for neural network models
Chryssolouris, G., Lee, M., & Ramsey, A. (1996) · IEEE Transactions on Neural Networks · doi:10.1109/72.478409 · Cited by 229
Xie, G., Wang, Q., Zeng, M., & Luo, L. Q. (2006) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2006.07.036 · Cited by 205
Dynamic prediction and control of heat exchangers using artificial neural networks
Dı́az, G., Sen, M., Yang, K. T., & McClain, R. L. (2001) · International Journal of Heat and Mass Transfer · doi:10.1016/s0017-9310(00)00228-3 · Cited by 151
Simulation of Heat Exchanger Performance by Artificial Neural Networks
Dı́az, G., Sen, M., Yang, K. T., & McClain, R. L. (1999) · Science and Technology for the Built Environment · doi:10.1080/10789669.1999.10391233 · Cited by 140
Diagnosis using backpropagation neural networks—analysis and criticism
Kramer, M. A., & Leonard, J. A. (1990) · Computers & Chemical Engineering · doi:10.1016/0098-1354(90)80015-4 · Cited by 138
İslamoğlu, Y. (2002) · Applied Thermal Engineering · doi:10.1016/s1359-4311(02)00155-2 · Cited by 137
A neural network methodology for heat transfer data analysis
Thibault, J., & Grandjean, B. P. A. (1991) · International Journal of Heat and Mass Transfer · doi:10.1016/0017-9310(91)90217-3 · Cited by 137
Heat transfer analysis using ANNs with experimental data for air flowing in corrugated channels
İslamoğlu, Y., & Kurt, A. V. (2003) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2003.07.031 · Cited by 122
Research works printed but not linked: 1
- Wang, 1994, A neural network adaptive control based on rapid learning method and its application, Adv. Model Anal., 46, 27
Cited by
Li, Q., Flamant, G., Yuan, X., Neveu, P., & Luo, L. (2011) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2011.07.066 · Cited by 323
Qasem, N. A. A., & Zubair, S. M. (2018) · Energy Conversion and Management · doi:10.1016/j.enconman.2018.06.104 · Cited by 134
Metadata
- Authors
- Peng, H., & Ling, X.
- Affiliations
- Nanjing Tech University (CN)
- Corresponding author
- Ling, Xiang
- ORCID
- Venue
- Applied Thermal Engineering
- Publisher
- Elsevier BV
- Published
- 2009-08
- Volume
- 29
- Issue
- 11-12
- Pages
- 2251-2256
- ISSN
- 1359-4311 (ISSN-L)
- OpenAlex
- W1992012920
- Cited by
- 78
- References
- 22
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 3 · 2023: 5 · 2022: 5 · 2021: 5 · 2020: 5 · 2019: 1 · 2018: 6 · 2017: 2 · 2016: 5 · 2015: 9 · 2014: 5 · 2013: 3 · 2012: 3
- FWCI
- 6.38
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Locations
- Applied Thermal Engineering (publishedVersion)
- Funders
- Vedecká Grantová Agentúra MŠVVaŠ SR a SAV
- Nanjing Tech University
- Program for New Century Excellent Talents in University
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Heat Transfer and Optimization
- Physical Sciences › Engineering › Mechanical Engineering › Heat Transfer Mechanisms
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
- Keywords
- plate-fin heat exchanger, artificial neural networks, pressure drop prediction, heat transfer prediction, Colburn factor, friction factor, fin geometry, feedforward neural networks, backpropagation, network architecture selection
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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.
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Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Neural networks analysis of thermal characteristics on plate-fin heat exchangers with limited experimental data. https://app.cochat.ai/papers/10.1016/j.applthermaleng.2008.11.011
- The paper
- Peng, H., & Ling, X. (2009). Neural networks analysis of thermal characteristics on plate-fin heat exchangers with limited experimental data. Applied Thermal Engineering. https://doi.org/10.1016/j.applthermaleng.2008.11.011
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
