Three-phase congestion prediction utilizing artificial neural networks
作者： Rafik Fainti , Miltiadis Alamaniotis , Lefteri H. Tsoukalas
DOI: 10.1109/IISA.2016.7785422
关键词:
摘要: The aim of this study is to develop and test a predictor capable projecting whether each phase power distribution line will be overloaded or not. Prediction implemented using an artificial neural network, which has been shown high accuracy efficiency in non-linear problems. In our work, the network trained Levenberg-Marquardt algorithm, while Bayesian regularization adopted order avoid overfitting input data. Results demonstrate capability predict congestion three-phase big data environment.
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