首页|Study Findings on Machine Learning Reported by a Researcher at Department of Ele ctrical Engineering and Industrial Informatics (Power Factor Modelling and Predi ction at the Hot Rolling Mills' Power Supply Using Machine Learning Algorithms)
Study Findings on Machine Learning Reported by a Researcher at Department of Ele ctrical Engineering and Industrial Informatics (Power Factor Modelling and Predi ction at the Hot Rolling Mills' Power Supply Using Machine Learning Algorithms)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Data detailed on artificial intelligence have bee n presented. According to news reporting out of Timisoara, Romania, by NewsRx ed itors, research stated, "The power supply is crucial in the present day due to t he negative impacts of poor power quality on the electric grid." The news journalists obtained a quote from the research from Department of Elect rical Engineering and Industrial Informatics: "In this research, we employed dee p learning methods to investigate the power factor, which is a significant indic ator of power quality. A multi-step forecast was developed for the power factor in the power supply installation of a hot rolling mill, extending beyond the hor izontal line. This was conducted using data obtained from the respective electri cal supply system. The forecast was developed via hybrid RNN (recurrent neural n etworks) incorporating LSTM (long short-term memory) and GRU (gated recurrent un it) layers. This research utilized hybrid recurrent neural network designs with deep learning methods to build several power factor models. These layers have ad vantages for time series forecasting."
Department of Electrical Engineering and Industrial InformaticsTimisoaraRomaniaEuropeAlgorithmsCyborgsEmergi ng TechnologiesMachine Learning
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