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A Novel Multiobjective Fireworks Algorithm and Its Applications to Imbalanced Distance Minimization Problems

IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1476-1489页

作者： Shoufei Han Kun Zhu MengChu Zhou Xiaojing Liu Haoyue Liu Yusuf Al-Turki Abdullah Abusorrah College of Computer Science and Technology Nanjing University of Aeronautics and Astronauticsand also with the Collaborative Innovation Center of Novel Software Technology and IndustrializationNanjing 211106China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of Engineeringand also with the K.A.CARE Energy Research and Innovation CenterKing Abdulaziz UniversityJeddah 21589Saudi Arabia

Recently,multimodal multiobjective optimization problems(MMOPs)have received increasing *** goal is to find a Pareto front and as many equivalent Pareto optimal solutions as *** some evolutionary algorithms for them have been proposed,they mainly focus on the convergence rate in the decision space while ignoring solutions *** this paper,we propose a new multiobjective fireworks algorithm for them,which is able to balance exploitation and exploration in the decision *** first extend a latest single-objective fireworks algorithm to handle *** we make improvements by incorporating an adaptive strategy and special archive guidance into it,where special archives are established for each firework,and two strategies(i.e.,explosion and random strategies)are adaptively selected to update the positions of sparks generated by fireworks with the guidance of special ***,we compare the proposed algorithm with eight state-of-the-art multimodal multiobjective algorithms on all 22 MMOPs from CEC2019 and several imbalanced distance minimization *** results show that the proposed algorithm is superior to compared algorithms in solving ***,its runtime is less than its peers'.

关键词： Adaptive strategy fireworks algorithm multimodal multiobjective optimization problems(MMOP)

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Pulsed Electromagnetic Field Interaction With a Transmission Line: An Analytical Traveling-Wave Approach Based on Reciprocity

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IEEE Transactions on Antennas and Propagation 2025年第6期73卷 3783-3791页

作者： Stumpf, Martin Antonini, Giulio Lager, Ioan E. Ekman, Jonas The Czech Republic Lerch Laboratory of em Research Department of Radio Electronics Feec Brno University of Technology Technická Brno3082/12 616 00 Czech Republic Luleå University of Technology Department of Computer Science Electrical and Space Engineering Eislab Luleå971 87 Sweden University of l'Aquila UAq Emc Laboratory Department of Industrial and Information Engineering and Economics L'Aquila671 00 Italy Delft University of Technology Terahertz Sensing Group Faculty of Electrical Engineering Mathematics and Computer Science Delft2628 CD Netherlands

Pulsed electromagnetic (EM) field signal transfer from a general EM source distribution to a transmission line (TL) is analyzed with the aid of Lorentz's reciprocity theorem. In this fashion, the transient voltage induced by the impulsive EM source is expressed through the EM fields as radiated by the TL. These transmitted EM fields are expressed in closed form using an analytical procedure that resembles the Cagniard-DeHoop (CdH) technique. The validity of the proposed reciprocity-based methodology is verified with the aid of an alternative analytical solution describing the EM field signal transfer excited by an impulsive vertical electric dipole (VED). Illustrative numerical examples are presented. © 1963-2012 IEEE.

关键词： Time domain analysis

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A Comparative Analysis of SiC MOSFET Performance in a Traction Inverter 20

A Comparative Analysis of SiC MOSFET Performance in a Tracti...

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20th IEEE Asia Pacific Conference on Circuits and systems and IEEE Asia Pacific Conference on Postgraduate research in Microelectronics Electronics, APCCAS and PrimeAsia 2024

作者： Wu, Chih-Chiang Rout, Uma Sankar Wang, Yu-Long Lin, Yi-Ling Hu, Jwu-Sheng National Yang Ming Chiao Tung University Department of Electrical Engineering & Computer Science Taiwan Industrial Technology Research Institute Mechanical and Mechatronics Systems Research Laboratories Hsinchu Taiwan

ISBN: (纸本)9798350378771

This study rigorously tests and verifies silicon carbide (SiC) power modules within a developed 800 V electric vehicle traction inverter. SiC traction inverters offer high efficiency, power density, and compact size. The developed SiCbased traction inverter is thoroughly evaluated on the established platform with various switching frequency, achieving a peak drive efficiency exceeding 98% at 6 kHz and a power density of 50 kW/L. © 2024 IEEE.

关键词： Power MOSFET

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Prediction of Battery Remaining useful Life: an approach using Kolmogorov-Arnold Network (KAN)

Prediction of Battery Remaining useful Life: an approach usi...

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International Conference on Green Energy, Computing and Intelligent Technology 2024, GEn-CITy 2024

作者： Yao, Kenneth Kong Zhi Wong, W.K. Gopal, Lenin Department of Electrical and Computer Engineering Curtin University Malaysia Miri Malaysia Connected Intelligence Research Group University of Southampton Malaysia Johor Iskandar Puteri79100 Malaysia

ISBN: (纸本)9781837242689

Lithium-ion batteries (LIBs) are extensively used across various applications, including electronic gadgets, electric vehicles (EVs), and residential energy storage systems. Despite their higher upfront costs, LIBs have become the go-to energy storage option, surpassing traditional technologies like lead-acid and flow batteries. This dominance is attributed to their notable characteristics, such as high energy density, extended lifespan, fast-charging capabilities, and minimal self-discharge, making them crucial for energy storage systems (ESS) in both commercial and industrial sectors. However, degradation of LIBs over time are due to two factors: 1) calendar ageing (results in a slow loss of capacity), and 2) cycling ageing, (which occurs from repeated charge and discharge cycles). Factors that affect these process includes extreme temperatures, high charge/discharge currents, and operation at extreme states of charge can accelerate this degradation. Due to this reason, it is imperative to find the remaining useful life of the battery as a preventive maintenance approach. The ammount of research in this area largely focuses on the deployment of various machine learning models. Recently, the machine learning community has revisited Kolmogorov-Arnold networks (KAN), positioning them as a competitive alternative to traditional feed-forward neural networks that use activation functions like ReLU and sigmoid. KAN is now being applied across various fields. In this study, it is used to predict the Remaining Useful Life (RUL) of batteries. The findings reveal that KAN outperforms several models, including support vector machines (SVM), linear regression, and feed-forward neural networks, achieving an R2 value of 0.983. © The Institution of engineering & Technology 2024.

关键词： Preventive maintenance

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Power Transformer Health Index (HI) Prediction using Kolmogorov-Arnold Network

Power Transformer Health Index (HI) Prediction using Kolmogo...

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International Conference on Green Energy, Computing and Intelligent Technology 2024, GEn-CITy 2024

作者： Ling, Sylvia Law Hui Wong, W.K. Gopal, Lenin Chew, I.M. Rama Abirami, K. Department of Electrical and Computer Engineering Curtin University Malaysia Miri Malaysia Connected Intelligence Research Group University of Southampton Malaysia Johor Iskandar Puteri79100 Malaysia

ISBN: (纸本)9781837242689

Power transformers are critical assets in electrical power systems, and ensuring their reliability and longevity is paramount to maintaining the stability of power grids. One of the most significant threats to transformer health is internal degradation, which can manifest through electrical and thermal stresses. Dissolved Gas Analysis (DGA) is a widely accepted method for diagnosing transformer health by detecting specific gases dissolved in the transformer oil. These gases, including hydrogen, methane, ethylene, and others, are by-products of insulation breakdown and oil degradation, which occur due to faults like partial discharge, arcing, and overheating. While traditional methods for interpreting DGA data, such as the Rogers Ratio, Duval Triangle, and Key Gas Method, have been valuable, they often rely on fixed thresholds or expert judgment, which can limit their accuracy and scalability. Recent advancements in machine learning (ML) offer a promising alternative by enabling data-driven approaches that can identify complex patterns and relationships within DGA features. Machine learning models can learn from historical data, providing more accurate and timely predictions of transformer health and fault conditions. This paper presents an ML approach for power transformer health assessment, employing the Kolmogorov-Arnold Network(KAN) model. The study leverages DGA data to train and evaluate the models, aiming to enhance accuracy in fault detection. KAN is used to capture the non-linear relationship and complexity within the DGA data, while Multilayer Perceptron (MLP) serves as a baseline for comparison. The simulation results show the KAN model with 3 layers (and a single univariate layer), with an RMSE of 0.0011 and R2 of 1.000 in independently reserved test data. This result significantly outperforms the MLP and demonstrates a superior ability to handle nonlinearities and reduce prediction error. © The Institution of engineering & Technology 2024.

关键词： Diagnosis

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Designing an Advanced Situational Awareness Platform Using Intelligent Multi-Drones for Smart Farming Towards Agriculture 5.0 11

Designing an Advanced Situational Awareness Platform Using I...

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Hermanus, Davy Ronald Supangkat, Suhono Harso Hidayat, Fadhil Bina Nusantara University Research Interest Group in Educational Technology Computer Science Department Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

ISBN: (纸本)9798350389654

With regard to Agriculture 5.0, the goal of this research is to create an intelligent platform for multi-drone collaboration that will improve situational awareness. This study examines the crucial phases in the Sensing, Understanding, and Action processes by fusing cutting-edge drone technology with creative coordination methods. Creating the architecture and foundation for drone collaboration, utilizing artificial intelligence for real-time data processing, and creating user interfaces that work are all part of the study technique. Area coverage, data quality, processing speed, and decision-making effectiveness are some of the performance evaluation measures. The goal of the research is to identify strategies for enhancing large-scale farming methods' resource management and operational effectiveness. The results will greatly enhance Agriculture 5.0 technologies and create avenues for the deployment of multi-drone collaboration platforms in a variety of high-situational awareness businesses. © 2024 IEEE.

关键词： Data quality

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Control of Microgrid Cluster Using Raspberry Pi

Control of Microgrid Cluster Using Raspberry Pi

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2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

作者： Carrasco-González, David Sarrias-Mena, Raúl Horrillo-Quintero, Pablo Llorens-Iborra, Francisco Fernández-Ramírez, Luis M. Suret Research Group Department of Electrical Engineering Algeciras Spain Uca Suret Reseach Group Dept. of Engineering in Automation Electronics and Computer Architecture and Networks Algeciras Spain

ISBN: (纸本)9781665471640

Currently, microgrid clusters (MGC) are being increasingly used owing to their benefits and human needs. MGs can be composed of power generation, consumption, and storage elements. They permit the combination of DC and AC technologies, even for a single microgrid (MG). In this paper, a new control system of a MGC consisting of two MGs connected to the main grid is developed. One of them is a DC MG that is composed of a wind turbine (WT), electrolyzer (EZ), ultracapacitor (UC), fuel cell (FC) and DC loads. The other MG is an AC MG, which is made up of a PV generator, a battery bank and AC loads. The MGC is tested under different working conditions in an experimental setup composed of a Raspberry Pi microcontroller, an OPAL-RT 4510 unit and a PC host. The experimental setup allows the system to run in real time and validate the results obtained. Finally, the control system implemented in the MGC exhibits a correct behaviour under different conditions, according to the results obtained. © 2023 IEEE.

关键词： energy management system Microgrid cluster Raspberry Pi real-time simulation

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GPU accelerated blockchain over key-value database transactions

IET Blockchain

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IET Blockchain 2022年第1期2卷 1-12页

作者： Iliakis, Konstantinos Koliogeorgi, Konstantina Litke, Antonios Varvarigou, Theodora Soudris, Dimitrios Microprocessors and Digital Systems Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Zografou Campous 9 Iroon Polytechniou str Athens Greece Distributed Knowledge and Media Systems group Department of Electrical and Computer Engineering National Technical University of Athens Zografou Campous 9 Iroon Polytechniou str Athens Greece

Blockchain is a distributed ledger based on peer-to-peer networks, originally used for crypto-currency systems. Blockchains are being used as an enabling technology for decentralised applications in the areas of Internet-of-Things, finance, supply-chain and others. Consistency, data privacy, performance, and energy efficiency are of paramount importance in such applications. The full nodes of public, permissionless blockchains undertake the task of verifying the transactions generated by the network. Full nodes perform operations such as confirming balances, transactions, and history, i.e. mostly database search queries. Consequently, their throughput is crucial for the performance of blockchain systems. In this work, the benefits of accelerating the blockchain search and insert queries by leveraging GPU platforms are studied. An extensive comparison between the most dominant utilized database is provided, i.e. LevelDB, and MegaKV, a high-performance GPU-accelerated database. Realistic operations that take place in blockchain systems are emulated and evaluated over representative scenarios, showing three orders of magnitude gains in throughput and energy efficiency without compromising the security aspect. The extensive comparison between LevelDB and MegaKV indicates that GPU acceleration is an effective solution for runtime and energy efficiency enhancement of blockchain systems, and the integration of the two technologies is a promising field of research. © 2022 The Authors. IET Blockchain published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Blockchain

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Partial Eigenvalues Assignment in Singular systems Using Brauer and Rado Eigenvalue Embedding for Impulse Elimination

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ASME Letters in Dynamic systems and Control 2024年第2期4卷 021001页

作者： Araújo, Jose M. Santos, Tito L.M. Signals and Systems Research Group Federal Institute of Bahia Rua Emıd´io dos Santos S/N Barbalho BA Salvador40301-015 Brazil Department of Electrical and Computer Engineering Federal University of Bahia Rua Arisides Novis 02 Federacão BA 40210-630 Brazil

A partial infinite eigenvalues assignment for singular systems is proposed, inspired by the well-known Brauer theorem for eigenvalue embedding. Removal of infinite eigenvalues is a frequent practice in mechanical systems, for instance, to avoid impulsive acceleration and dangerous jerk of the system degrees-of-freedom with null or highly unbalanced mass. Recent efforts were delivered to extend the Brauer theorem to the generalized singular regular eigenvalue problem. However, removing infinite eigenvalues is treated as a particular example by taking the reciprocal pencil and removing its null eigenvalues. In this note, proof for partial infinite eigenvalues removal is made directly in the original regular singular pencil by updating the descriptor matrix, with no need to take the reciprocal pencil. Multi-step and single-step procedures for impulsive response elimination using Brauer's and Rado's type finite eigenvalues embedding are presented. The obtained results are effective, as illustrated in a numerical example. Copyright © 2024 by ASME.

关键词： Linear systems

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Cross-cultural contextualisation for recommender systems

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Journal of Ambient Intelligence and Humanized Computing 2024年第2期15卷 1659-1670页

作者： Hong, Minsung An, Sojung Akerkar, Rajendra Camacho, David Jung, Jason J. Big Data Research Group Western Norway Research Institute Vestlandsforsking Sogndal6851 Norway Department of Computer Science and Engineering Chung-Ang University 84 Heukseok-ro Heukseok-dong Dongjak-gu Seoul Korea Republic of Information Systems Department Technical University of Madrid Madrid28031 Spain

Cultural Heritage (CH) domain is rapidly moving from traditional heritage sites into smart cultural heritage environment through various technologies. As one of the important technologies in the smart space, Recommender systems (RSs) have been widely utilised to personalised services and matching visitors’ goals and behaviours. Whereas, cultural difference is often considered a barrier to technology transfer or adoption. However, few studies focus on how the cultural factor influences recommendation despite cultural difference largely affects user preferences in the RSs. Furthermore, existing researches have mainly analysed evaluation results of their recommendation to reveal cultural differences, rather than utilising the cross-cultural factors into RSs. In this paper, we propose a novel concept of cross-cultural contextualisation and a model to compute the cross-cultural factor affecting users (countries or cultures) preferences by using matrix factorisation and clustering techniques. In addition, we discuss how to apply the model to RSs in CH domain through cross-domain recommendation techniques. Note that the two computational techniques were used to analyse cross-cultural factors which impact to user preferences, rather than to recommend items. In other words, the proposed model and computing results capable of utilisation into the other RSs as well as various research fields. Results of experiments with a real-world dataset showed effectiveness of the proposed model and supported that there is cultural difference influencing users’ rating behaviours. Furthermore, a systematic analysis of dataset and the experimental results presented that individual users could be considered as country-wise groups for the model to analyse the cross-cultural factors. © Springer-Verlag GmbH Germany, part of Springer Nature 2019.

关键词： Recommender systems

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