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Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Aidong Zhao Xianan Wang Zixiao Lin Zhaori Bi Xudong Li Changhao Yan Fan Yang Li Shang Dian Zhou Xuan Zeng State Key Laboratory of Integrated Chips and Systems Microelectronics Department Fudan University Shanghai China Department of Electrical Engineering University of Texas at Dallas USA Department of Electrical and Computer Engineering University of California at San Diego USA School of Data Science Fudan University Shanghai China School of Computer Science Fudan University Shanghai China

ISBN: (纸本)9798350323481

A constrained Voronoi tree-based domain decomposition method for high-dimensional Bayesian optimization is proposed to solve large scale analog circuit synthesis problems, which can be formulated as high-dimensional heterogeneous black-box optimization. Hierarchical Voronoi tree progressively breaks down the design space into partitions with implicit performance boundaries such that promising regions are efficiently explored. Fast exploitation is ensured in Voronoi nest via local Bayesian optimization with a few observations. A slice-enhanced Gibbs sampling method is proposed to sample acquisition function cMES in irregular polyhedrons with design constraints. Compared with state-of-the-art methods, cVTS achieves significant speed up without loss of accuracy.

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Hinge-Wasserstein: Estimating Multimodal Aleatoric Uncertainty in Regression Tasks

arXiv

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arXiv 2023年

作者： Xiong, Ziliang Jonnarth, Arvi Eldesokey, Abdelrahman Johnander, Joakim Wandt, Bastian Forssén, Per-Erik Computer Vision Laboratory Department of Electrical Engineering LiU Sweden Visual Computing Center KAUST Saudi Arabia Husqvarna Group Huskvarna Sweden Zenseact Sweden

computer vision systems that are deployed in safety-critical applications need to quantify their output uncertainty. We study regression from images to parameter values and here it is common to detect uncertainty by predicting probability distributions. In this context, we investigate the regression-by-classification paradigm which can represent multimodal distributions, without a prior assumption on the number of modes. Through experiments on a specifically designed synthetic dataset, we demonstrate that traditional loss functions lead to poor probability distribution estimates and severe overconfidence, in the absence of full ground truth distributions. In order to alleviate these issues, we propose hinge-Wasserstein – a simple improvement of the Wasserstein loss that reduces the penalty for weak secondary modes during training. This enables prediction of complex distributions with multiple modes, and allows training on datasets where full ground truth distributions are not available. In extensive experiments, we show that the proposed loss leads to substantially better uncertainty estimation on two challenging computer vision tasks: horizon line detection and stereo disparity estimation. The code is available at:https://***/XZLeo/ hinge-Wasserstein Copyright © 2023, The Authors. All rights reserved.

关键词： Probability distributions

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CPS, Sustainability and Efficiency in an Aquaponic Greenhouse

Renewable Energy and Power Quality Journal

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Renewable Energy and Power Quality Journal 2022年 20卷 210-215页

作者： Galvão, J. Santos, P. Aires, L. Neves, F. Department of Electrical Engineering/ESTG Polytechnic of Leiria Leiria2411-901 Portugal LSRE-LCM-Laboratory of Separation and Reaction Engineering Laboratory of Catalysis and Materials Escola Superior de Tecnologia e Gestão Instituto Politécnico de Leiria Leiria2411-901 Portugal ALiCE-Associate Laboratory in Chemical Engineering Faculty of Engineering University of Porto Rua Dr. Roberto Frias Porto4200-465 Portugal R&D Unit Institute for Systems Engineering and Computers/INESC Coimbra Portugal Department of Computer Science Polytechnic of Leiria Leiria2411-901 Portugal

Nowadays the humanity needs to produce food in greater quantity and quality, in order to satisfy citizens and markets, supported by advanced technologies such as cyber-physical system (CPS) or intelligent systems where software and electronic devices and receivers of physical variables are mechanisms that control the management of multiple actions inherent to plant growth. Electronic devices and receivers of physical variables are mechanisms that involve a network of IoT components and control multiple actions inherent to plant growth in agricultural greenhouses, which in short, are intensive food production systems. In this context, this paper presents a case study that uses a monitoring and management system that considers environmental parameters measured inside a greenhouse, allowing the manager to assess the working status of an aquaponic systems, and detect critical conditions that require quick decisions in real time. It is intended to develop technology that can be used in greenhouses, close to consumer centres or cities, to mitigate the impact of transport, lowering CO2 emissions resulting from the distribution channels between the producers and consumers. © 2022, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Energy efficiency

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Machine Learning for Scalable and Optimal Load Shedding Under Power System Contingency

arXiv

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arXiv 2024年

作者： Zhou, Yuqi Zhu, Hao Power Systems Engineering Center National Renewable Energy Laboratory GoldenCO80401 United States Department of Electrical & Computer Engineering The University of Texas at Austin AustinTX78712 United States

Prompt and effective corrective actions in response to unexpected contingencies are crucial for improving power system resilience and preventing cascading blackouts. The optimal load shedding (OLS) accounting for network limits has the potential to address the diverse system-wide impacts of contingency scenarios as compared to traditional local schemes. However, due to the fast cascading propagation of initial contingencies, real-time OLS solutions are challenging to attain in large systems with high computation and communication needs. In this paper, we propose a decentralized design that leverages offline training of a neural network (NN) model for individual load centers to autonomously construct the OLS solutions from locally available measurements. Our learning-for-OLS approach can greatly reduce the computation and communication needs during online emergency responses, thus preventing the cascading propagation of contingencies for enhanced power grid resilience. Numerical studies on both the IEEE 118-bus system and a synthetic Texas 2000-bus system have demonstrated the efficiency and effectiveness of our scalable OLS learning design for timely power system emergency operations. Copyright © 2024, The Authors. All rights reserved.

关键词： Electric power plant loads

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Analytical Model for Device Currents in 5-Level Active Neutral Point Clamped Converter

Analytical Model for Device Currents in 5-Level Active Neutr...

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International Conference on electrical systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC)

作者： Daniel Zakzewski Rakesh Resalayyan Apurv Kumar Yadav Alireza Khaligh Department of Electrical and Computer Engineering Maryland Power Electronics Laboratory The Institute for Systems Research University of Maryland College Park United States Department of Electrical Engineering Indian Institute of Technology Roorkee Uttrakhand India

This paper presents a closed form analytical model for semiconductor and capacitor currents in a 5-Level Active Neutral Point Clamped Converter (5L-ANPC) topology. This model enables device selection, performance prediction, and design optimization of the topology. Models for the switch and FC currents are derived based on the topology's switching states. A model for input capacitor current is derived by analyzing the interaction of three phase legs of the topology. The model is verified using conventional time-domain switching simulation of the topology.

关键词： Semiconductor device modeling Analytical models Capacitors Transportation Stars Switches Predictive models

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Explainable Application Intent for Zero-Touch Networking: An Incorporation of Hypergraph and Transformer

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IEEE Transactions on Communications 2025年

作者： Wu, Bing Zou, Sai Liwang, Minghui Ni, Wei Wang, Xianbin Guizhou University College of Big Data and Information Engineering China National Key Laboratory of Autonomous Intelligent Unmanned Systems Department of Control Science and Engineering China Tongji University Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai China Data61 CSIRO Australia Department of Electrical and Computer Engineering Western University Canada

The autonomous interpretation of application intent (APPI) represents the primary step towards achieving closed-loop autonomy in zero-touch networking (ZTN) and also a prerequisite for intent-based networking (IBN). However, understanding APPIs and invoking the corresponding network resources require network professionals with extensive technical expertise to customize network service requests (NSRs), which presents significant challenges for the large-scale deployment of ZTN. This paper investigates an interesting problem of autonomous interpretation of APPIs for ZTN, where a novel mechanism integrating hypergraph and transformer with completeness assurance (HyperTrans-CA) is proposed. In particular, we first involve the Bayesian theory to model APPIs interpretability as maximizing the correct transition probability, where hypergraph is used to describe the complex relationship between application characteristics (e.g., scenario function, and performance) and NSRs, including network devices, virtual network functions (VNFs), and resources. Then, the hypergraph is integrated into the encoder, decoder, and attention mechanisms of Transformer, and a completeness assurance mechanism is designed to improve the prediction accuracy. The convergence of HyperTrans-CA and the corresponding convergence speed of the hypergraph-boosted Transformer in the graph search process are also analyzed. Comprehensive simulations and empirical measurements regarding industrial internet demonstrate that HyperTrans-CA can effectively explain/understand APPIs. Compared to the state-of-the-art Transformer and ChatGPT3.5 models, HyperTrans-CA improves the prediction accuracy of APPIs mapped to VNFs by 23% and 46%, respectively, while raising the prediction accuracy of VNF locations by 8.6 and 17.3 times. © 2025 IEEE.

关键词： Bayesian networks

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Assessing the Efficacy of Improved Learning in Hourly Global Irradiance Prediction

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computers, Materials & Continua 2023年第11期77卷 2579-2594页

作者： Abdennasser Dahmani Yamina Ammi Nadjem Bailek Alban Kuriqi Nadhir Al-Ansari Salah Hanini Ilhami Colak Laith Abualigah El-Sayed M.El-kenawy Department of Mechanical Engineering Faculty of Science and TechnologyGIDD Industrial Engineering and Sustainable Development LaboratoryUniversity of RelizaneBourmadiaRelizane48000Algeria Laboratory of Biomaterials and Transport Phenomena(LBMPT) University of MedeaUrban PoleMedea26000Algeria Energies and Materials Research Laboratory Faculty of Sciences and TechnologyUniversity of TamanghassetTamanrasset10034Algeria Sustainable Development and Computer Science Laboratory Faculty of Sciences and TechnologyAhmed Draia University of AdrarAdrarAlgeria CERIS Instituto Superior TécnicoUniversidade de LisboaLisbon1049-001Portugal Civil Engineering Department University for Business and TechnologyPristina10000Kosovo Department of Civil Environmental and Natural Resources EngineeringLulea University of TechnologyLulea97187Sweden Engineering and Architecture Faculty Nisantasi UniversityIstanbulTurkey Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl al-Bayt UniversityMafraq25113Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan MEU Research Unit Middle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains MalaysiaPulau Pinang11800Malaysia Department of Computing and Information Systems School of Engineering and TechnologySunway University MalaysiaPetaling Jaya27500Malaysia Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt

Increasing global energy consumption has become an urgent problem as natural energy sources such as oil,gas,and uranium are rapidly running *** into renewable energy sources such as solar energy is being pursued to counter *** energy is one of the most promising renewable energy sources,as it has the potential to meet the world’s energy needs *** study aims to develop and evaluate artificial intelligence(AI)models for predicting hourly global *** hyperparameters were optimized using the Broyden-FletcherGoldfarb-Shanno(BFGS)quasi-Newton training algorithm and STATISTICA *** from two stations in Algeria with different climatic zones were used to develop the *** error measurements were used to determine the accuracy of the prediction models,including the correlation coefficient,the mean absolute error,and the root mean square error(RMSE).The optimal support vector machine(SVM)model showed exceptional efficiency during the training phase,with a high correlation coefficient(R=0.99)and a low mean absolute error(MAE=26.5741 Wh/m^(2)),as well as an RMSE of 38.7045 Wh/m^(2) across all ***,this study highlights the importance of accurate prediction models in the renewable energy,which can contribute to better energy management and planning.

关键词： Renewable energy energy prediction global irradiation artificial intelligence BFGS quasi-Newton training algorithm

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Design and Implementation of Links Generation for Inter Domain Routing System 12

Design and Implementation of Links Generation for Inter Doma...

引用

12th International Conference on Information Science and Technology, ICIST 2022

作者： Wang, Yu Qiao, Zhi Yin, Junru Zhang, Mingliang College of Software Henan University of Engineering Zhengzhou China College of Information and Electrical Engineering China Agriculture University Beijing China College of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Network Research Department Zhengzhou China

ISBN: (数字)9781665485821

ISBN: (纸本)9781665485821

Due to the inherent flaws of BGP protocol, the security of inter domain routing system has been regularly threatened. Since it is difficult to achieve collaborative defense against existing resources and strategies of multiple autonomous systems, this paper designs and organizes them into autonomous system community. Within the community, a precomputing multi-link generation mechanism is proposed based on genetic algorithm. Before the inter domain routing system is attacked, the link set can be generated as complete as possible in advance. Once an attack occurs, the community will quickly select proper precomputing links to replace the failed ones, in order to ensure the stability of inter domain communication. The effectiveness of the mechanism has been proved in function and performance through simulation experiments. © 2022 IEEE.

关键词： Genetic algorithms

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An Optimal Bipolar MVDC Coaxial Power Cable Design for Envisaged All Electric Wide Body Aircraft

An Optimal Bipolar MVDC Coaxial Power Cable Design for Envis...

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Conference on electrical Insulation and Dielectric Phenomena, (CEIDP)

作者： Anoy Saha Arian Azizi Mona Ghassemi Department of Electrical and Computer Engineering Zero Emission Realization of Optimized Energy Systems (ZEROES) Laboratory The University of Texas at Dallas Richardson TX USA

Future generations of electrified aircraft, such as more electric aircraft (MEA) and all-electric aircraft (AEA), will require high-power-delivery and low-system-mass electric power systems (EPS). Designing aircraft cables confronts thermal challenges due to the limited heat transfer by convection at a cruising altitude of 12.2 km (18.8 kPa) for wide-body aircraft. These thermal challenges are exacerbated by implementing bipolar MVDC EPSs which are formed of two adjacent power cables, conventionally. In this regard, coaxial geometry for cables can be evaluated as a solution to this problem. In this paper, a coaxial MVDC power cable is, for the first time, designed with inner and outer conductors carrying the same ampacity of 1000 A when the voltage of the inner and outer conductors is −5 kV and +5 kV, respectively. This design compares the effectiveness of coaxial power cables to the conventional arrangement of bipolar MVDC cable systems. This study will analyze three case studies to determine if a coaxial geometry is better than a conventional arrangement for a bipolar MVDC cable system or not. According to the findings of this study, coaxial cable requires thicker insulation and more conductors to maintain the same maximum electric field norm within cable insulation and ampacity. As a result, coaxial cables result in a greater mass and cross-sectional area than standard bipolar cables. For the envisaged AEA, the investigation in this paper addresses questions about the performance of coaxial geometry for bipolar MVDC power cables.

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Transmission Expansion Planning (TEP)-Based Unconventional High Surge Impedance Loading (HSIL) Line Design Concept

Transmission Expansion Planning (TEP)-Based Unconventional H...

引用

Annual North-American Power Symposium

作者： Babak Porkar Mona Ghassemi Mushfiqul Abedin Khan Department of Electrical and Computer Engineering Zero Emission Realization of Optimized Energy Systems (ZEROES) Laboratory The University of Texas at Dallas Richardson TX USA

This paper develops a new concept that we call transmission expansion planning (TEP)-based unconventional high surge impedance loading (HSIL) line design. To date, these two areas (TEP and transmission line design) have been conducted separately. For TEP, planners typically use the electrical parameters of a few standard conventional line designs to study planning scenarios, and then, the final candidate line is constructed. In such a sequence, cost-effective scenarios often do not meet the technical criteria of load flow. In this paper, we will study whether this sequence can be overturned; namely, can a transmission expansion planner get optimal line parameter values that lead to the most cost-effective scenario, and then have a transmission line with those parameters be designed? Although this cannot currently be realized through conventional designs, in this paper, we demonstrate that it is a possibility if breakthrough designs for transmission lines are used by shifting phase configurations and subconductors into unconventional HSIL arrangements, leading to the optimal line parameters determined by TEP.

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