1. Sequence-to-Sequence models and their evaluation for spoken language normalization of SlovenianMirjam Sepesy Maučec, Darinka Verdonik, Gregor Donaj, 2024, original scientific article Keywords: low-resource language, applications, spoken language, normalization, character unit, subword unit, statistical model, long short-term memory, transformer, error analysis Published in DKUM: 31.01.2025; Views: 0; Downloads: 5
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2. Electrical and Electromechanical Converters : Lecture NotationsIvan Zagradišnik, Jožef Ritonja, 2025 Abstract: The publication is divided into five chapters: Introduction: magnetic field, excitation of windings, induction of voltage, forces and torque, conversion of electrical power into electrical or mechanical power, losses, efficiency, heating and cooling. Transformer: construction elements, ideal and real single-phase transformer, three-phase transformer, special transformer designs. Induction machine: description of construction with windings and mode of operation, starting motors and varying speed and torque, induction generator, single-phase induction motors. Synchronous machine: description of construction and operation, operation on a rigid grid, approximate treatment of a saturated machine, excitation systems and the use of permanent magnets for excitation, and permanent magnet synchronous motors. Keywords: fundamentals of electromagnetics, transformer, induction machine, synchronous machine, commutator machine Published in DKUM: 17.01.2025; Views: 0; Downloads: 22
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3. A Machine Learning Application for the Energy Flexibility Assessment of a Distribution Network for ConsumersJaka Rober, Leon Maruša, Miloš Beković, 2023, original scientific article Keywords: flexibility, baseline, demand response, distribution transformer, congestion management, power flow control, peak shaving, load shifting, predictive models, machine learning Published in DKUM: 05.01.2024; Views: 386; Downloads: 58
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6. Parameter identification of the Jiles-Atherton hysteresis model using differental evolutionMatej Toman, Gorazd Štumberger, Drago Dolinar, 2008, original scientific article Abstract: In this paper, parameters of the Jiles-Atherton (J-A) hysteresis model are identified using a stochastic search algorithm called differential evolution (DE). The J-A hysteresis model's parameters are identified by DE in such a way, that best possible agreement is obtained between the measured and model calculated hysteresis loops. This agreement is furthermore increased by improving the J-A hysteresis model. The improvement is achieved by replacing a constant pinning parameter in the J-A hysteresis model with a variable one. Here, the variable pinning parameter is written as a function of a magnetic field. Bz DE identified parameters are used in the J-A hysteresis model, which is included in the dynamic model of a single-phase transformer. The effectiveness of the improved J-A hysteresis model and parameters identification approach is verified with experiments and simulations. Keywords: Jiles-Atherton model, J-A hysteresis model, magnetic hysteresis, optimization methods, parameters estimation, single-phase transformer Published in DKUM: 31.05.2012; Views: 2146; Downloads: 107
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