Iskanje po katalogu digitalne knjižnice

Opis: This paper deals with determining the accuracy of measuring systems for determining the characteristics of rotating electrical machines. Efficiency classes and experimental methods for determining efficiency, are given in a standard, which has to be strictly respected. For determining the efficiency of an electrical machine, it is necessary to have a modern and accurate measurement system with sensors of high accuracy classes, which enables the user to carry out precise measurements and consequently, to determine all the characteristics of the electrical machine. This paper will be focused on torque and speed measurements.
Ključne besede: efficiency, measuring system, electric machines, torque and rotational sensors, accuracy
Objavljeno v DKUM: 04.12.2023; Ogledov: 529; Prenosov: 30
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Opis: This paper assesses the fault-detection capabilities of modern deep-learning models. It highlights that a naive deep-learning approach optimized for accuracy is unsuitable for learning fault-detection models from time-series data. Consequently, out-of-the-box deep-learning strategies may yield impressive accuracy results but are ill-equipped for real-world applications. The paper introduces a methodology for estimating fault-detection delays when no oracle information on fault occurrence time is available. Moreover, the paper presents a straightforward approach to implicitly achieve the objective of minimizing fault-detection delays. This approach involves using pseudo-multi-objective deep optimization with data windowing, which enables the utilization of standard deep-learning methods for fault detection and expanding their applicability. However, it does introduce an additional hyperparameter that needs careful tuning. The paper employs the Tennessee Eastman Process dataset as a case study to demonstrate its findings. The results effectively highlight the limitations of standard loss functions and emphasize the importance of incorporating fault-detection delays in evaluating and reporting performance. In our study, the pseudo-multi-objective optimization could reach a fault-detection accuracy of 95% in just a fifth of the time it takes the best naive approach to do so.
Ključne besede: artificial neural networks, deep learning, fault detection, accuracy, multi-objective optimization
Objavljeno v DKUM: 30.11.2023; Ogledov: 363; Prenosov: 27
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Opis: Real parameter optimization problems are often very complex and computationally expensive. We can find such problems in engineering and scientific applications. In this paper, a new algorithm is proposed to tackle the 100-Digit Challenge. There are 10 functions representing 10 optimization problems, and the goal is to compute each function’s minimum value to 10 digits of accuracy. There is no limit on either time or the maximum number of function evaluations. The proposed algorithm is based on the self-adaptive differential evolution algorithm jDE. Our algorithm uses two populations and some other mechanisms when tackling the challenge. We provide the score for each function as required by the organizers of this challenge competition.
Ključne besede: differential evolution, optimization, global optimum, accuracy
Objavljeno v DKUM: 23.01.2023; Ogledov: 543; Prenosov: 24
Celotno besedilo (425,62 KB)
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Opis: This paper brings to light an economic problem that frequently appears in practice: For the same variable, more alternative forecasts are proposed, yet the decision-making process requires the use of a single prediction. Therefore, a forecast assessment is necessary to select the best prediction. The aim of this research is to propose some strategies for improving the unemployment rate forecast in Romania by conducting a comparative accuracy analysis of unemployment rate forecasts based on two quantitative methods: Kalman filter and vector-auto-regressive (VAR) models. The first method considers the evolution of unemployment components, while the VAR model takes into account the interdependencies between the unemployment rate and the inflation rate. According to the Granger causality test, the inflation rate in the first difference is a cause of the unemployment rate in the first difference, these data sets being stationary. For the unemployment rate forecasts for 2010-2012 in Romania, the VAR models (in all variants of VAR simulations) determined more accurate predictions than Kalman filter based on two state space models for all accuracy measures. According to mean absolute scaled error, the dynamic-stochastic simulations used in predicting unemployment based on the VAR model are the most accurate. Another strategy for improving the initial forecasts based on the Kalman filter used the adjusted unemployment data transformed by the application of the Hodrick-Prescott filter. However, the use of VAR models rather than different variants of the Kalman filter methods remains the best strategy in improving the quality of the unemployment rate forecast in Romania. The explanation of these results is related to the fact that the interaction of unemployment with inflation provides useful information for predictions of the evolution of unemployment related to its components (i.e., natural unemployment and cyclical component).
Ključne besede: forecasts, accuracy, Kalman filter, Hodrick-Prescott filter, VAR models, unemployment rate
Objavljeno v DKUM: 13.11.2017; Ogledov: 1816; Prenosov: 391
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Opis: This paper investigates the role of the Berlitz method of teaching English in today's language education. The Berlitz method has been present in the English language area for a long time and the principal objective of this diploma thesis was to prove that even today, it is a very successful and effective method of teaching English, whose characteristics should be implemented in language classrooms around the world. The first part of my thesis introduces the history of English language teaching and the history of the Berlitz method. Characteristics of the Berlitz method, its development and the role in today's education are presented. The second part, which is also the principal part of the thesis, draws upon lesson observations of three children’s and two adult classes which I did at the Berlitz language centre in Maribor. The data collected here focused on three aspects of the didactical triangle: the teacher, the learner and the content. Important information about each segment is introduced, with the emphasis on the content, the use of teaching aids, the role of fluency and accuracy, the rapport between teachers and learners and about motivation in Berlitz classes. The last part of my thesis involves information about Berlitz kids’ camps and a survey which reveals some significant information about the teachers’ and learners’ experiences and views on the Berlitz method.
Ključne besede: English language teaching, the Berlitz method, lesson observations, the content, teaching aids, fluency and accuracy, rapport, motivation, Berlitz kids' camps.
Objavljeno v DKUM: 08.07.2013; Ogledov: 2981; Prenosov: 185
Celotno besedilo (653,75 KB)