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Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Electrical and Computer Engineering

TÜBİTAK

2018

Neural networks

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

Symbolic Interpretation Of Artificial Neural Networks Using Genetic Algorithms, Dounia Yedjour, Abdelkader Benyettou, Hayat Yedjour Jan 2018

Symbolic Interpretation Of Artificial Neural Networks Using Genetic Algorithms, Dounia Yedjour, Abdelkader Benyettou, Hayat Yedjour

Turkish Journal of Electrical Engineering and Computer Sciences

The knowledge acquired during the learning of artificial neural networks (ANNs) is coded as values in synaptic weights, which makes their interpretations difficult, hence the name of the black box. The aim of this work is to provide a comprehensible interpretation of the ANN's decisions by extracting symbolic rules. We improve the performance of our extraction algorithm by combining the ANN with a genetic algorithm. Misleading rules whose support and confidence values are less than fixed thresholds are removed and, as a result, the comprehensibility is improved. The extracted rules are evaluated and compared with other works. The results show …


Multilabel Learning For The Online Transient Stability Assessment Of Electric Power Systems, Peyman Beyranvand, Veysel Murat İstemi̇han Genç, Zehra Çataltepe Jan 2018

Multilabel Learning For The Online Transient Stability Assessment Of Electric Power Systems, Peyman Beyranvand, Veysel Murat İstemi̇han Genç, Zehra Çataltepe

Turkish Journal of Electrical Engineering and Computer Sciences

Dynamic security assessment of a large power system operating over a wide range of conditions requires an intensive computation for evaluating the system's transient stability against a large number of contingencies. In this study, we investigate the application of multilabel learning for improving training and prediction time, along with the prediction accuracy, of neural networks for online transient stability assessment of power systems. We introduce a new multilabel learning method, which uses a contingency clustering step to learn similar contingencies together in the same multilabel multilayer perceptron. Experimental results on two different power systems demonstrate improved accuracy, as well as …