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Periodica polytechnica Electrical engineering and computer science 2022年第3期66卷 215-226页

作者： Al-Sudany, Huda Naji Lantos, Béla Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics P.O.B. 91 BudapestH-1521 Hungary

Development of an Adaptive Fuzzy Extended Kalman Filter (AFEKF) and an Adaptive Fuzzy Unscented Kalman Filter (AFUKF) for the state estimation of unmanned aerial vehicles (UAVs) were presented in this paper based on real flight data of a fixed wing airplane. The Adaptive Neuro Fuzzy extension helps to estimate the values of the EKF's and UKF's Rkcovariance matrix at each sampling instant when measurement update step is carried out. The ANFIS monitors the EKF's and UKF's performances attempt to eliminate the gap between theoretical and real innovation sequences' covariance. The investigations show that AFUKF can provide better performance in accuracy and less error than the AFEKF in case of real flight data for maneuvering fixed wing UAVs. © 2022 Budapest University of Technology and Economics. All rights reserved.

关键词： Extended Kalman filters

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Energy Quality Analysis of Electrical Drive Systems with Induction Machine 17

Energy Quality Analysis of Electrical Drive Systems with Ind...

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17th International Conference on engineering of Modern Electric Systems, EMES 2023

作者： Silaghi, Helga Spoiala, Viorica Costea, Claudiu Magdoiu, Liliana Gamec, Jan Silaghi, Alexandru Marius University of Oradea Control Systems Engineering and Management Department Oradea Romania Technical University of Kosice Faculty of Electrical Engineering and Informatics Kosice Slovakia University of Oradea Electrical Engineering Department Oradea Romania

ISBN: (纸本)9798350310634

Inthis paper many improvements in dealing with energy quality issues that could arise in electrical drive systems using asynchronous machines are presented. A series active power filter is used in electrical drive systems with induction motors to reduce harmonic current and voltage. We also propose a variety of active power filters with hysteresis current value control. Lastly, some experimental results for an electrical drive system utilizing an induction motor and a PWM converter are provided. These findings are followed by a discussion of the system's energy quality issues. © 2023 IEEE.

关键词： Induction machine

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ATDN vSLAM: An All-Through Deep Learning-Based Solution for Visual Simultaneous Localization and Mapping

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2022年第3期66卷 236-247页

作者： Szántó, Mátyás Bogár, György Richárd Vajta, László Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics 2 Magyar tudosok Blvd. BudapestH-1117 Hungary

In this paper, a novel solution is introduced for visual Simultaneous Localization and Mapping (vSLAM) that is built up of Deep Learning components. The proposed architecture is a highly modular framework in which each component offers state of the art results in their respective fields of vision-based Deep Learning solutions. The paper shows that with the synergic integration of these individual building blocks, a functioning and efficient all-through deep neural (ATDN) vSLAM system can be created. The Embedding Distance Loss function is introduced and using it the ATDN architecture is trained. The resulting system managed to achieve 4.4% translation and 0.0176 deg/m rotational error on a subset of the KITTI dataset. The proposed architecture can be used for efficient and lowlatency autonomous driving (AD) aiding database creation as well as a basis for autonomous vehicle (AV) control. © 2022 Budapest University of Technology and Economics. All rights reserved.

关键词： Autonomous vehicles

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Estimating Chlorophyll Content from Hyperspectral Data Using Gradient Features 23rd

Estimating Chlorophyll Content from Hyperspectral Data Usin...

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23rd International Conference on Computational Science, ICCS 2023

作者： Ruszczak, Bogdan Wijata, Agata M. Nalepa, Jakub Faculty of Electrical Engineering Automatic Control and Informatics Department of Informatics Opole University of Technology Opole Poland Faculty of Biomedical Engineering Silesian University of Technology Zabrze Poland Faculty of Automatic Control Electronics and Computer Science Department of Algorithmics and Software Silesian University of Technology Gliwice Poland KP Labs Gliwice Poland

ISBN: (纸本)9783031360206

Non-invasive estimation of chlorophyll content in plants plays an important role in precision agriculture. This task may be tackled using hyperspectral imaging that acquires numerous narrow bands of the electromagnetic spectrum, which may reflect subtle features of the plant, and inherently offers spatial scalability. Such imagery is, however, high-dimensional, therefore it is challenging to transfer from the imaging device, store and investigate. We propose a machine learning pipeline for estimating chlorophyll content from hyperspectral data. It benefits from the Savitzky-Golay filtering to smooth the (potentially noisy) spectral curves, and from gradient-based features extracted from such a smoothed signal. The experiments revealed that our approach significantly outperforms the state of the art according to the widely-established estimation quality metrics obtained for four chlorophyll-related parameters. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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Machine Learning-Based Calibration Approaches for Single-Beam and Multiple-Beam Distance Sensors

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IEEE Sensors Journal 2024年第1期24卷 975-983页

作者： Syu, Jia-Hao Lin, Jerry Chun-Wei Biernacki, Piotr Ziebinski, Adam National Taiwan University Department of Computer Science and Information Engineering Taipei10617 Taiwan Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Department of Distributed Systems and Informatics Devices Gliwice44-100 Poland Silesian University of Technology Department of Distributed Systems and Informatic Devices Gliwice44-100 Poland

Sensors are the foundation to facilitate smart cities, smart grids, and smart transportation, and distance sensors are especially important for sensing the environment and gathering information. Researchers have developed various methods to calibrate distance sensors;however, they mainly focus on using external information for calibration, which is inefficient and computationally expensive. To alleviate the above problems, we propose machine learning (ML)-based calibration approaches for distance sensors. We develop two calibration mechanisms, where the naive mechanism directly predicts the true distance, while the residual mechanism predicts the residual for calibration. The conventional ML regression algorithms are then adopted to predict the true distance or calibration residual. Experimental results show that the designed residual calibration mechanism outperforms the naive mechanism by reducing the root mean square error (RMSE) by 92.2% and mean absolute error (MAE) by 93.3% in the fitting task. In prediction, the proposed 2-D-residual mechanism achieves an improvement of 78.6% and 65.7% compared to the state-of-the-art method. The experimental results show the effectiveness and generalization of the proposed ML-based calibration method, especially for the 2-D mechanism, which achieves the highest robustness in all fitting and prediction tasks. © 2001-2012 IEEE.

关键词： Calibration

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A Review on Electric Vehicles Charging Strategies concerning Actors Interests

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2022年第2期66卷 148-162页

作者： Sabzi, Shahab Vajta, Laszlo Faghihi, Tayebeh Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary

Electric vehicles are becoming increasingly popular in societies and an important part of smart grids. Utility companies should be able to provide them with vital energy as they need electric energy instead of fuel, and this is where new challenges emerge in the network. In order to avoid causing utilities to incur additional energy and economic losses, researchers have proposed smart charging as a way to provide adequate energy to vehicles. When developing a charging schedule for a fleet of EVs, special considerations are made on variables such as energy, cost, and EVs milage. In this review paper, the importance of EVs integration into smart grids is studied, and then different methods to develop EVs charging scheduling are investigated. These methods can vary from optimization algorithms to learning-based, and game theory-based approaches. Then, as the considered system consists of three main actors, including EV users, the utility operator, and aggregators, a systematic review is conducted on these actors, and objectives related to each one are analyzed. Finally, research gaps related to the problem are studied. Researchers can use this review to conduct further research on the integration of EVs into smart grids. © 2022 Budapest University of Technology and Economics. All rights reserved.

关键词： Electric vehicles

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Exploring the Use of Particle and Kalman Filters for Obstacle Detection in Mobile Robots

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2023年第4期67卷 384-393页

作者： Gyenes, Zoltán Bölöni, Ladislau Szádeczky-Kardoss, Emese Gincsainé Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Muegyetem rkp. 3. BudapestH-1111 Hungary Department of Computer Science University of Central Florida 4328 Scorpius St OrlandoFL32816-2362 United States

The present study aims to explore the adaptation of estimation methodologies, specifically Particle filters and Kalman filters, for the purpose of determining the position and velocity vector of obstacles within the operational workspace of mobile robots. These algorithms are commonly employed in the motion planning tasks of mobile robots for the estimation of their own position. The proposed methodology utilizes LiDAR sensor data to estimate the position vectors and calculate the velocity vectors of obstacles. Additionally, an uncertainty parameter can be determined using the introduced perception method. The performance of the newly adapted algorithms is evaluated through comparison of the absolute error in position and velocity vector estimations. © 2023 Budapest University of Technology and Economics. All rights reserved.

关键词： Mobile robots

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Accounting for Non-Uniform Ambient Lighting in Ray Traced Ambient Occlusion

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2022年第3期66卷 248-252页

作者： Fridvalszky, András Tóth, Balázs Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Muegyetem rkp. 3. BudapestH-1111 Hungary

Ambient occlusion is a popular method to enhance the visuals of real-time applications. The generally accepted equation assumes that incoming ambient lighting is uniform in the enclosing hemisphere around the surface point. This assumption does not always hold and can cause artifacts. With screen-space techniques the artifact may not be present, because of the lack of information, but it becomes visible with more accurate methods. This is especially true for ray tracing based implementations which are widely used to create the ground truth image to measure other techniques. With recent advancements of the graphics hardware, they also found their way into real-time applications where these shortcomings were neither discussed nor addressed. In this paper we analyze the problem and demonstrate its presence in popular game engines. We also propose a ray tracing based extension to eliminate these artifact in a physically plausible way. © 2022 Budapest University of Technology and Economics. All rights reserved.

关键词： Ray tracing

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NLP-Assisted Educational Memory Game Experiment 13th

NLP-Assisted Educational Memory Game Experiment

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13th International Conference on Methodologies and Intelligent Systems for Technology Enhanced Learning, mis4TEL 2023

作者： Burkus, Viktória Kárpáti, Attila Szécsi, László Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. Budapest1111 Hungary

ISBN: (纸本)9783031421334

Memory card games are well-known for everyone. Their main goal is to find matching pairs among flipped cards by simultaneously turning two cards up. In each round information obtained and memorized from the previous round is used to predict matching pair positions. Whilst playing, a player’s thinking, memory, concentration, and attention skills can be improved, therefore, incorporating it into the learning process may be beneficial to the learner. In this research, we present a method for learning terminology from a scientific context by playing an AI-generated memory card game. We employ a general-purpose conversation chatbot, ChatGPT to generate the keyword-description pairs from a given scientific text. The primary purpose of our study is to evaluate the outcomes, with respect to their scientific accuracy and educational value. Consequently, we present a straightforward approach to constructing a game that facilitates the acquisition of knowledge by students in an enjoyable and playful way. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Natural language processing systems

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Ontological Decision Support Model for Cargo Port Risk Management 7

Ontological Decision Support Model for Cargo Port Risk Manag...

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7th International Conference on Information, control, and Communication Technologies, ICCT 2023

作者： Bondareva, Irina Protalinskiy, Oleg Khanova, Anna Nesterova, Evgeniya Belova, Anastasiya Astrakhan State Technical University Department of Applied Informatics Astrakhan Russia Moscow Power Engineering Institute Department of Automated Control Systems of Thermal Processes Moscow Russia

ISBN: (纸本)9798350340945

Modern unstable conditions of the market environment dictate the need for transport logistics enterprises to predict possible risk situations in order to prevent them, as well as to develop tools that allow forming management decisions, evaluating the effectiveness of each of them and choosing the most appropriate one, taking into account specific tasks and various influencing factors. As risks, situations of failure to achieve the goals of the cargo port, as well as failure to achieve standard values by the indicators for assessing these goals are considered. Goals and indicators are indicated in the constructed balanced scorecard (BSC). A set of links between goals and indicators for their assessment with risks at various levels of management is presented in the form of a developed multi-level hybrid logical-probabilistic (LP) risk model of the cargo port, as well as in detailed scenario models of this LP model. The ontological model contains all the information about the interaction of elements that affect the onset of risky events, and allows you to select options for exiting a risky situation in accordance with various specified conditions. The simulation model allows, based on the results of requests to the ontological model and the scenarios of simulation experiments developed on their basis, to develop a management decision that allows avoiding risky situations in the longer term, taking into account all available stochastic characteristics and factors of influence. © 2023 IEEE.

关键词： Risk management

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