The DOI matches its Crossref record, with a small difference in title or year; 126 of the 126 references it cites were found in a registry or an index.
Methodologies in power systems fault detection and diagnosis
Overview
Integrity signals
Registry
Cites
Statistics
Verification
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?
In the citing paper
“80% of faults occur in distribution lines; hence, this area is of particular importance for researchers [3].”
From Fault Detection and Fault Diagnosis in Power System Using AI: A Review (2024) · cites this paper as [15]
Citations
Cites
Neural Networks: A Comprehensive Foundation
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Book Review: Pattern Recognition and Machine Learning
Nasrabadi, N. M. (2007) · Journal of Electronic Imaging · doi:10.1117/1.2819119 · Cited by 22,066
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Schölkopf, B., & Smola, A. J. (2001) · The MIT Press eBooks · doi:10.7551/mitpress/4175.001.0001 · Cited by 11,703
Chandola, V., Banerjee, A., & Kumar, V. (2009) · ACM Computing Surveys · doi:10.1145/1541880.1541882 · Cited by 11,687
A comparison of methods for multiclass support vector machines
Hsu, C., & Lin, C. (2002) · IEEE Transactions on Neural Networks · doi:10.1109/72.991427 · Cited by 6,923
Estimating the Support of a High-Dimensional Distribution
Schölkopf, B., Platt, J. C., Shawe-Taylor, J., Smola, A. J., & Williamson, R. C. (2001) · Neural Computation · doi:10.1162/089976601750264965 · Cited by 6,168
Nazuno, J. F. (2000) · Computación y Sistemas · Cited by 3,201
A review of process fault detection and diagnosis
Venkatasubramanian, V., Rengaswamy, R., Yin, K., & Kavuri, S. N. (2003) · Computers & Chemical Engineering · doi:10.1016/s0098-1354(02)00160-6 · Cited by 2,723
Hand, D. J., Mannila, H., & Smyth, P. (2001) · Cited by 2,581
Research works printed but not linked: 4
- Wang, C.: Methodologies and algorithms for fault locators in modern power systems. Ph.D. dissertation, University of the West of England, UK (2002)
- Haque, M., Kashtiban, A.: Application of neural networks in power system: a review. Trans. Eng. Comput. Technol. 6 (2000)
- Bishop, C.: Pattern recognition and machine learning. Available online http://books.google.com.pk/books?id=kTNoQgAACAAJ . Information Science and Statistics, Springer (2006)
- Steinwart, I., Christmann, A.: Support vector machines (information science & statistics). Recherche 67, 02 (2008)
Cited by
Davari, N., Akbarizadeh, G., & Mashhour, E. (2021) · IEEE Transactions on Power Delivery · doi:10.1109/tpwrd.2020.3046161 · Cited by 106
Fault Detection and Fault Diagnosis in Power System Using AI: A Review
Nasim, S. F., Aziz, S., Qaiser, A., Kulsoom, U., & Ahmed, S. (2024) · Sir Syed University Research Journal of Engineering & Technology · doi:10.33317/ssurj.598 · Cited by 17
Metadata
- Authors
- Aleem, S. A., Shahid, N., & Naqvi, I. H.
- Affiliations
- University of Pennsylvania (US)
- École Polytechnique Fédérale de Lausanne (CH)
- Lahore University of Management Sciences (PK)
- Corresponding author
- Aleem, Saad Abdul
- Venue
- Energy Systems
- Published
- 2014-06-07
- Volume
- 6
- Issue
- 1
- Pages
- 85-108
- ISSN
- 1868-3967 (ISSN-L)
- 1868-3975
- OpenAlex
- W2040160862
- Cited by
- 83
- References
- 126
- Citations by year
- 2026: 4 · 2025: 19 · 2024: 16 · 2023: 12 · 2022: 11 · 2021: 9 · 2020: 4 · 2019: 3 · 2018: 1 · 2017: 3 · 2015: 1
- FWCI
- 1.49
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Energy Systems (publishedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Power Systems Fault Detection
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Power System Optimization and Stability
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electrical Fault Detection and Protection
- Keywords
- power system fault detection, fault diagnosis, fault classification, transmission line faults, pattern recognition, wavelet transform, artificial neural networks, support vector machine, unsupervised learning, process history
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.
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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.
