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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A cluster-based dissimilarity learning approach for localized fault classification in Smart Grids
Enrico De Santis, Antonello Rizzi, Alireza Sadeghian
Swarm and Evolutionary Computation (2017) Vol. 39, pp. 267-278
Closed Access | Times Cited: 22

Showing 22 citing articles:

Machine learning driven smart electric power systems: Current trends and new perspectives
Muhammad Sohail Ibrahim, Wei Dong, Qiang Yang
Applied Energy (2020) Vol. 272, pp. 115237-115237
Closed Access | Times Cited: 297
Faults in smart grid systems: Monitoring, detection and classification
Angel Esteban Labrador Rivas, Taufik Abrão
Electric Power Systems Research (2020) Vol. 189, pp. 106602-106602
Closed Access | Times Cited: 161
Machine learning applications in power system fault diagnosis: Research advancements and perspectives
Rachna Vaish, U. D. Dwivedi, Saurabh Tewari, et al.
Engineering Applications of Artificial Intelligence (2021) Vol. 106, pp. 104504-104504
Closed Access | Times Cited: 103
Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review
Faiaz Ahsan, Nazia Hasan Dana, Subrata K. Sarker, et al.
Protection and Control of Modern Power Systems (2023) Vol. 8, Iss. 1
Open Access | Times Cited: 57
Systematic review of energy theft practices and autonomous detection through artificial intelligence methods
Erika Stracqualursi, Antonello Rosato, Gianfranco Di Lorenzo, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 184, pp. 113544-113544
Open Access | Times Cited: 20
Modeling failures in smart grids by a bilinear logistic regression approach
Enrico De Santis, Antonello Rizzi
Neural Networks (2024) Vol. 174, pp. 106245-106245
Open Access | Times Cited: 2
Hierarchical evolutionary classification framework for human action recognition using sparse dictionary optimization
R. Jansi, R. Amutha
Swarm and Evolutionary Computation (2021) Vol. 63, pp. 100873-100873
Closed Access | Times Cited: 9
Random forest based power sustainability and cost optimization in smart grid
Danalakshmi Durairaj, Łukasz Wróblewski, Sheela Androse Joseph, et al.
Production Engineering Archives (2022) Vol. 28, Iss. 1, pp. 82-92
Open Access | Times Cited: 6
A Comparative Study of Smart Grid Security Based on Unsupervised Learning and Load Ranking
Shuva Paul, Md. Rashedul Haq, Avijit Das, et al.
(2019)
Closed Access | Times Cited: 8
A Supervised Classification System based on Evolutive Multi-Agent Clustering for Smart Grids Faults Prediction
Mauro Giampieri, Enrico De Santis, Antonello Rizzi, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2018), pp. 1-8
Closed Access | Times Cited: 7
Modelling and Recognition of Protein Contact Networks by Multiple Kernel Learning and Dissimilarity Representations
Alessio Martino, Enrico De Santis, Alessandro Giuliani, et al.
Entropy (2020) Vol. 22, Iss. 7, pp. 794-794
Open Access | Times Cited: 6
Estimation of fault probability in medium voltage feeders through calibration techniques in classification models
Enrico De Santis, Francesco Arnò, Antonello Rizzi
Soft Computing (2022) Vol. 26, Iss. 15, pp. 7175-7193
Open Access | Times Cited: 4
On component-wise dissimilarity measures and metric properties in pattern recognition
Enrico De Santis, Alessio Martino, Antonello Rizzi
PeerJ Computer Science (2022) Vol. 8, pp. e1106-e1106
Open Access | Times Cited: 4
Discrimination of high impedance fault in microgrid power network using semi-supervised machine learning algorithm
Arangarajan Vinayagam, S. T. Suganthi, C. B. Venkatramanan, et al.
Ain Shams Engineering Journal (2024), pp. 103187-103187
Open Access
Hybrid optimized artificial neural network using Latin hypercube sampling and Bayesian optimization for detection, classification and location of faults in transmission lines
Abdul Yussif Seidu, Elvis Twumasi, Emmanuel Asuming Frimpong
AIMS Electronics and Electrical Engineering (2024) Vol. 8, Iss. 4, pp. 498-531
Open Access
Evolutionary Optimization of an Affine Model for Vulnerability Characterization in Smart Grids
Enrico De Santis, Maurizio Paschero, Antonello Rizzi, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2018), pp. 1-8
Closed Access | Times Cited: 3
An Information Granulation Approach Through m-Grams for Text Classification
Enrico De Santis, Antonino Capillo, Emanuele Ferrandino, et al.
Studies in computational intelligence (2023), pp. 73-89
Closed Access | Times Cited: 1
Random Forest Based Power Sustainability and Cost Optimization in Smart Grid
D. Danalakshmi, Łukasz Wróblewski, A. Sheela, et al.
(2022)
Open Access | Times Cited: 2
Introduction to Evolutionary Data Clustering and Its Applications
Ibrahim Aljarah, Maria Habib, Hossam Faris, et al.
Algorithms for intelligent systems (2021), pp. 1-21
Closed Access | Times Cited: 2
Review of Smart Grid Failure Prediction and the Need for its Study in STEM Careers
Marcelo Fabian Guato Burgos, Jorge Morato, Paulina Vizcaíno-Imacaña
Lecture notes in educational technology (2023), pp. 186-199
Closed Access
Modelling Failures in Smart Grids by a Bilinear Logistic Regression Approach
Enrico De Santis, Antonello Rizzi
(2023)
Closed Access
Prediction and Classification for Smart Grid Applications
Manoj Singh Adhikari, Ahmed Alkhayyat
Intelligent systems reference library (2023), pp. 87-102
Closed Access
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